Re: [Computer-go] New paper by DeepMind

[Jim O'Flaherty]

Tysvm for your excellent explanation.

And now you can see why I mentioned Google's being a member of OIN as a
critical distinction. It strongly increases the weight of 2. And implicitly
reduces the motivation for 1.


On Sat, Dec 8, 2018, 8:51 PM 甲斐徳本  Those are the points not well understood commonly.
>
> A patent application does two things.  1. Apply for an eventual granting
> of the patent, 2. Makes what's described in it a public knowledge as of the
> date of the filing.
> Patent may be functionally meaningless.  There may be no one to sue.  And
> these are huge issues for the point No.1.  However, a strategic patent
> applicants file patent applications for the point No.2 to deny any
> possibility of somebody else obtaining a patent.  (A public knowledge
> cannot be patented.)
>
> Many companies are trying to figure out how to patent DCNN based AI, and
> Google may be saying "Nope, as long as it is like the DeepMind method, you
> can't patent it."   Google is likely NOT saying "We are hoping to obtain
> the patent, and intend to enforce it."
>
> Despite many differences in patent law from a country to another, two
> basic purposes of patent are universal: 1. To protect the inventor, and 2.
> To promote the use of inventions by making the details a public knowledge.
>
>
>
>
> On Sat, Dec 8, 2018 at 12:47 AM uurtamo  wrote:
>
>> What I'm saying is that the patent is functionally meaningless. Who is
>> there to sue?
>>
>> Moreover, there is no enforceable patent on the broad class of algorithms
>> that could reproduce these results. No?
>>
>> s.
>>
>> On Fri, Dec 7, 2018, 4:16 AM Jim O'Flaherty > wrote:
>>
>>> Tysvm for the clarification, Tokumoto.
>>>
>>> On Thu, Dec 6, 2018, 8:02 PM 甲斐徳本 >>
>>>> What's insane about it?
>>>> To me, what Jim O'Flaherty stated is common sense in the field of
>>>> patents, and any patent attorney would attest to that.  If I may add, Jim's
>>>> last sentence should read "Google's patent application" instead of
>>>> "Google's patent".  The difference is huge, and this may be in the heart of
>>>> the issue, which is not well understood by the general public.
>>>>
>>>> In other words, thousands of patent applications are filed in the world
>>>> without any hope of the patent eventually being granted, to establish
>>>> "prior art" thereby protecting what's described in it from being patented
>>>> by somebody else.
>>>>
>>>> Or, am I responding to a troll?
>>>>
>>>> Tokumoto
>>>>
>>>>
>>>> On Fri, Dec 7, 2018 at 10:01 AM uurtamo  wrote:
>>>>
>>>>> You're insane.
>>>>>
>>>>> On Thu, Dec 6, 2018, 4:13 PM Jim O'Flaherty <
>>>>> jim.oflaherty...@gmail.com wrote:
>>>>>
>>>>>> Remember, patents are a STRATEGIC mechanism as well as a legal
>>>>>> mechanism. As soon as a patent is publically filed (for example, as
>>>>>> utility, and following provisional), the text and claims in the patent
>>>>>> immediately become prior art globally as of the original filing date
>>>>>> REGARDLESS of whether the patent is eventually approved or rejected. 
>>>>>> IOW, a
>>>>>> patent filing is a mechanism to ensure no one else can make a similar 
>>>>>> claim
>>>>>> without risking this filing being used as a possible prior art 
>>>>>> refutation.
>>>>>>
>>>>>> I know this only because it is a strategy option my company is using
>>>>>> in an entirely different unrelated domain. The patent filing is defensive
>>>>>> such that someone else cannot make a claim and take our inventions away
>>>>>> from us just because the coincidentally hit near our inventions.
>>>>>>
>>>>>> So considering Google's past and their participation in the OIN, it
>>>>>> is very likely Google's patent is ensuring the ground all around this 
>>>>>> area
>>>>>> is sufficiently salted to stop anyone from attempting to exploit nearby
>>>>>> patent claims.
>>>>>>
>>>>>>
>>>>>> Respectfully,
>>>>>>
>>>>>> Jim O'Flaherty
>>>>>>
>>>>>>
>>>>>> On T

Re: [Computer-go] New paper by DeepMind

[Jim O'Flaherty]

Tysvm for the clarification, Tokumoto.

On Thu, Dec 6, 2018, 8:02 PM 甲斐徳本  What's insane about it?
> To me, what Jim O'Flaherty stated is common sense in the field of patents,
> and any patent attorney would attest to that.  If I may add, Jim's last
> sentence should read "Google's patent application" instead of "Google's
> patent".  The difference is huge, and this may be in the heart of the
> issue, which is not well understood by the general public.
>
> In other words, thousands of patent applications are filed in the world
> without any hope of the patent eventually being granted, to establish
> "prior art" thereby protecting what's described in it from being patented
> by somebody else.
>
> Or, am I responding to a troll?
>
> Tokumoto
>
>
> On Fri, Dec 7, 2018 at 10:01 AM uurtamo  wrote:
>
>> You're insane.
>>
>> On Thu, Dec 6, 2018, 4:13 PM Jim O'Flaherty > wrote:
>>
>>> Remember, patents are a STRATEGIC mechanism as well as a legal
>>> mechanism. As soon as a patent is publically filed (for example, as
>>> utility, and following provisional), the text and claims in the patent
>>> immediately become prior art globally as of the original filing date
>>> REGARDLESS of whether the patent is eventually approved or rejected. IOW, a
>>> patent filing is a mechanism to ensure no one else can make a similar claim
>>> without risking this filing being used as a possible prior art refutation.
>>>
>>> I know this only because it is a strategy option my company is using in
>>> an entirely different unrelated domain. The patent filing is defensive such
>>> that someone else cannot make a claim and take our inventions away from us
>>> just because the coincidentally hit near our inventions.
>>>
>>> So considering Google's past and their participation in the OIN, it is
>>> very likely Google's patent is ensuring the ground all around this area is
>>> sufficiently salted to stop anyone from attempting to exploit nearby patent
>>> claims.
>>>
>>>
>>> Respectfully,
>>>
>>> Jim O'Flaherty
>>>
>>>
>>> On Thu, Dec 6, 2018 at 5:44 PM Erik van der Werf <
>>> erikvanderw...@gmail.com> wrote:
>>>
>>>> On Thu, Dec 6, 2018 at 11:28 PM Rémi Coulom 
>>>> wrote:
>>>>
>>>>> Also, the AlphaZero algorithm is patented:
>>>>> https://patentscope2.wipo.int/search/en/detail.jsf?docId=WO2018215665
>>>>>
>>>>
>>>> So far it just looks like an application (and I don't think it will be
>>>> be difficult to oppose, if you care about this)
>>>>
>>>> Erik
>>>>
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Re: [Computer-go] New paper by DeepMind

[Jim O'Flaherty]

Remember, patents are a STRATEGIC mechanism as well as a legal mechanism.
As soon as a patent is publically filed (for example, as utility, and
following provisional), the text and claims in the patent immediately
become prior art globally as of the original filing date REGARDLESS of
whether the patent is eventually approved or rejected. IOW, a patent filing
is a mechanism to ensure no one else can make a similar claim without
risking this filing being used as a possible prior art refutation.

I know this only because it is a strategy option my company is using in an
entirely different unrelated domain. The patent filing is defensive such
that someone else cannot make a claim and take our inventions away from us
just because the coincidentally hit near our inventions.

So considering Google's past and their participation in the OIN, it is very
likely Google's patent is ensuring the ground all around this area is
sufficiently salted to stop anyone from attempting to exploit nearby patent
claims.


Respectfully,

Jim O'Flaherty


On Thu, Dec 6, 2018 at 5:44 PM Erik van der Werf 
wrote:

> On Thu, Dec 6, 2018 at 11:28 PM Rémi Coulom  wrote:
>
>> Also, the AlphaZero algorithm is patented:
>> https://patentscope2.wipo.int/search/en/detail.jsf?docId=WO2018215665
>>
>
> So far it just looks like an application (and I don't think it will be be
> difficult to oppose, if you care about this)
>
> Erik
>
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Re: [Computer-go] Breakthrough: FineArt beating Ke Jie with 2 Handicap Stones

[Jim O'Flaherty]

Wow! Tysvm for the explicit _online_ game record.

White was FineArt. And Ke Jie, even granted a two stone handicap, lost in a
reading contest in a life/death struggle between two groups leading to the
resignation by move 78. That's astounding!


Namaste,

Jim O'Flaherty
Founder/CEO
QA Locate <http://www.qalocate.com/> • Irving, TX, USA
469-358-0633 <4693580633> • jim.oflaherty...@gmail.com •
www.linkedin.com/in/jimoflahertyjr

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On Sun, Jan 21, 2018 at 11:07 AM, Steven Clark <steven.p.cl...@gmail.com>
wrote:

> Not according to this: http://eidogo.com/#EUexCx07
> via reddit
>
> On Sun, Jan 21, 2018 at 11:54 AM, Jim O'Flaherty <
> jim.oflaherty...@gmail.com> wrote:
>
>> So the AI FineArt is assumed to have taken black with a two stone
>> handicap?
>>
>> On Jan 21, 2018 9:41 AM, "Michael Alford" <m...@aracnet.com> wrote:
>>
>>> This is the problem we had with the link to the IGF article.  The sense
>>> we made of the statement attributed to Ke Jie was he can't give FineArt h2
>>> because it is as strong as he is.  Thanks, Ingo, for the iink to the
>>> forum.  I have the games and will share them.
>>>
>>> Michael
>>>
>>> On 1/21/18 6:22 AM, Jim O'Flaherty wrote:
>>>
>>> It's unclear to me who played black with the two handicap stones.  Ke
>>> Jie or FineArt?
>>>
>>> On Jan 21, 2018 1:56 AM, Ingo Althöfer <3-hirn-ver...@gmx.de> wrote:
>>>
>>>> Stefan Kaitschick posted this in the German computer go forun:
>>>> http://www.dgob.de/yabbse/index.php?topic=6728.msg215694#msg215694
>>>>
>>>> His text roughly translated to English:
>>>> > I downloaded FineArt free 2 stone games.
>>>> > At least the game of Ke Jies is included.
>>>> > Perhaps this is (essentially) the collection.
>>>> > You have to rename the downloaded file to new ending .zip
>>>>
>>>> Hope this helps, Ingo.
>>>>
>>>>
>>>> > Gesendet: Sonntag, 21. Januar 2018 um 05:49 Uhr
>>>> > Von: "Michael Alford" <m...@aracnet.com>
>>>> > An: computer-go@computer-go.org
>>>> > Betreff: Re: [Computer-go] Breakthrough: FineArt beating Ke Jie with
>>>> 2 Handicap Stones
>>>> >
>>>> > Could someone make sgf's of these games available?
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>>>
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Re: [Computer-go] Breakthrough: FineArt beating Ke Jie with 2 Handicap Stones

[Jim O'Flaherty]

So the AI FineArt is assumed to have taken black with a two stone handicap?

On Jan 21, 2018 9:41 AM, "Michael Alford" <m...@aracnet.com> wrote:

> This is the problem we had with the link to the IGF article.  The sense we
> made of the statement attributed to Ke Jie was he can't give FineArt h2
> because it is as strong as he is.  Thanks, Ingo, for the iink to the
> forum.  I have the games and will share them.
>
> Michael
>
> On 1/21/18 6:22 AM, Jim O'Flaherty wrote:
>
> It's unclear to me who played black with the two handicap stones.  Ke Jie
> or FineArt?
>
> On Jan 21, 2018 1:56 AM, Ingo Althöfer <3-hirn-ver...@gmx.de> wrote:
>
>> Stefan Kaitschick posted this in the German computer go forun:
>> http://www.dgob.de/yabbse/index.php?topic=6728.msg215694#msg215694
>>
>> His text roughly translated to English:
>> > I downloaded FineArt free 2 stone games.
>> > At least the game of Ke Jies is included.
>> > Perhaps this is (essentially) the collection.
>> > You have to rename the downloaded file to new ending .zip
>>
>> Hope this helps, Ingo.
>>
>>
>> > Gesendet: Sonntag, 21. Januar 2018 um 05:49 Uhr
>> > Von: "Michael Alford" <m...@aracnet.com>
>> > An: computer-go@computer-go.org
>> > Betreff: Re: [Computer-go] Breakthrough: FineArt beating Ke Jie with 2
>> Handicap Stones
>> >
>> > Could someone make sgf's of these games available?
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Re: [Computer-go] difficult things for alphazero

[Jim O'Flaherty]

Dave,

To whom is the "your" in your first sentence referring? There is no context
from which to derive to whom you are speaking.


On Thu, Dec 7, 2017 at 3:30 PM, Dave Dyer  wrote:

>
> Without reference to your specific ideas for games that might be
> difficult to solve, I wonder where these games fit on the human
> playability scale.   The things we find acceptable as games are
> in a pretty small domain, which lies between the things that are
> trivial and the things that are too hard.
>
> There are lots of very hard problems, which are not games, which I bet
> the owners of Alphazero are interested in attacking next.
>
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Re: [Computer-go] AlphaGo Zero SGF - Free Use or Copyright?

[Jim O'Flaherty]

It's related to this line of thinking by Douglas Hoffstadter:
https://en.wikipedia.org/wiki/Copycat_(software)


Namaste,

Jim O'Flaherty
Founder/CEO
Precision Location Intelligence, Inc.
<http://www.precisionlocationintelligence.com/> • Irving, TX, USA
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On Thu, Oct 26, 2017 at 11:43 AM, Xavier Combelle <xavier.combe...@gmail.com
> wrote:

> what are semantic genetic algorithm ?
>
> to my knowledge genetic algorithm lead to poor result except as a
> metaheuristic in optimisation problem
>
> Le 26/10/2017 à 14:40, Jim O'Flaherty a écrit :
>
> When I get time to spend dozens of hours on computer go again, I plan to
> play in Robert's area with semantic genetic algorithms. I am an Architect
> Software Engineer. Robert's work will allow me better than starting
> entirely from random in much the same way AlphaGo bootstrapped from the
> 100K of professional games. AG0 then leveraged AlphaGo in knowing an
> architecture that was close enough. My intuition is my approach will be
> something similar in it's evolution.
>
> This is the way we're going to "automate" creating provided proofing of
> human cognition styled computer go players to assist humans in a gradient
> ascent learning cycle.
>
> So, Robert, I admire and am encouraged by your research for my own
> computer go projects in this area. Keep kicking butt in your unique way. We
> are in an interesting transition in this community. Stick it out. It will
> be worth it long term.
>
> On Oct 26, 2017 4:38 AM, "Petri Pitkanen" <petri.t.pitka...@gmail.com>
> wrote:
>
>> Unfortunately there is no proof that you principles work better than
>> those form eighties. Nor there is any agreement that your pronciples form
>> any improvement over the old ones. Yes you are a  far better player than me
>> and shows that you are
>> - way better at reading
>> - have hugely better go understanding, principles if you like
>>
>> What is missing that I doubt that you can verbalise your go understanding
>> to degree that by applying those principles  I could become substantially
>> better player. again bulleting
>> - My reading skills would not get any better hence making much of value
>> any learning moot. Obviously issue on me not on your principles
>> - your principles are more complex than you understand. Much of you know
>> is automated to degree that it is subconsciousness information.
>> Transferring that information if hard. Usually done by re-playing master
>> games looking at problems i.e. training the darn neural net in the head
>>
>> If you can build Go bot about  KGS 3/4dan strength I am more than willing
>> to admit you are right and would even consider buying your  books.
>>
>> Petri
>>
>> 2017-10-26 6:21 GMT+03:00 Robert Jasiek <jas...@snafu.de>:
>>
>>> On 25.10.2017 18:17, Xavier Combelle wrote:
>>>
>>>> exact go theory is full of hole.
>>>>
>>>
>>> WRT describing the whole game, yes, this is the current state. Solving
>>> go in a mathematical sense is a project for centuries.
>>>
>>> Actually, to my knowledge human can't apply only the exact go theory and
>>>> play a decent game.
>>>>
>>>
>>> Only for certain positions of a) late endgame, b) semeais, c) ko.
>>>
>>> If human can't do that, how it will teach a computer to do it magically ?
>>>>
>>>
>>> IIRC, Martin Müller implemented CGT endgames a la Mathematical Go
>>> Endgames.
>>>
>>> The reason why (b) had became unpopular is because there is no go theory
>>>> precise enough to implement it as an algorithm
>>>>
>>>
>>> There is quite some theory of the 95% principle kind which might be
>>> implemented as approximation. E.g. "Usually, defend your weak important
>>> group.&quo

Re: [Computer-go] AlphaGo Zero SGF - Free Use or Copyright?

[Jim O'Flaherty]

When I get time to spend dozens of hours on computer go again, I plan to
play in Robert's area with semantic genetic algorithms. I am an Architect
Software Engineer. Robert's work will allow me better than starting
entirely from random in much the same way AlphaGo bootstrapped from the
100K of professional games. AG0 then leveraged AlphaGo in knowing an
architecture that was close enough. My intuition is my approach will be
something similar in it's evolution.

This is the way we're going to "automate" creating provided proofing of
human cognition styled computer go players to assist humans in a gradient
ascent learning cycle.

So, Robert, I admire and am encouraged by your research for my own computer
go projects in this area. Keep kicking butt in your unique way. We are in
an interesting transition in this community. Stick it out. It will be worth
it long term.

On Oct 26, 2017 4:38 AM, "Petri Pitkanen" 
wrote:

> Unfortunately there is no proof that you principles work better than those
> form eighties. Nor there is any agreement that your pronciples form any
> improvement over the old ones. Yes you are a  far better player than me and
> shows that you are
> - way better at reading
> - have hugely better go understanding, principles if you like
>
> What is missing that I doubt that you can verbalise your go understanding
> to degree that by applying those principles  I could become substantially
> better player. again bulleting
> - My reading skills would not get any better hence making much of value
> any learning moot. Obviously issue on me not on your principles
> - your principles are more complex than you understand. Much of you know
> is automated to degree that it is subconsciousness information.
> Transferring that information if hard. Usually done by re-playing master
> games looking at problems i.e. training the darn neural net in the head
>
> If you can build Go bot about  KGS 3/4dan strength I am more than willing
> to admit you are right and would even consider buying your  books.
>
> Petri
>
> 2017-10-26 6:21 GMT+03:00 Robert Jasiek :
>
>> On 25.10.2017 18:17, Xavier Combelle wrote:
>>
>>> exact go theory is full of hole.
>>>
>>
>> WRT describing the whole game, yes, this is the current state. Solving go
>> in a mathematical sense is a project for centuries.
>>
>> Actually, to my knowledge human can't apply only the exact go theory and
>>> play a decent game.
>>>
>>
>> Only for certain positions of a) late endgame, b) semeais, c) ko.
>>
>> If human can't do that, how it will teach a computer to do it magically ?
>>>
>>
>> IIRC, Martin Müller implemented CGT endgames a la Mathematical Go
>> Endgames.
>>
>> The reason why (b) had became unpopular is because there is no go theory
>>> precise enough to implement it as an algorithm
>>>
>>
>> There is quite some theory of the 95% principle kind which might be
>> implemented as approximation. E.g. "Usually, defend your weak important
>> group." can be approximated by approximating "group", "important" (its loss
>> is too large in a quick positional judgement), "weak" (can be killed in two
>> successive moves), "defend" (after the move, cannot be killed in two
>> successive moves), "usually" (always, unless there are several such groups
>> and some must be chosen, say, randomly; the approximation being that the
>> alternative strategy of large scale exchange is discarded).
>>
>> Besides, one must prioritise principles to solve conflicting principles
>> by a higher order principle.
>>
>> IMO, such an expert system combined with tree reading and maybe MCTS to
>> emulate reading used when a principle depends on reading can, with an
>> effort of a few manyears of implementation, already achieve amateur mid
>> dan. Not high dan yet because high dans can choose advanced strategies,
>> such as global exchange, and there are no good enough principles for that
>> yet, which would also consider necessary side conditions related to
>> influence, aji etc. I need to work out such principles during the following
>> years. Currently, the state is that weaker principles have identified the
>> major topics (influence, aji etc.) to be considered in fights but they must
>> be refined to create 95%+ principles.
>>
>> ***
>>
>> In the 80s and 90s, expert systems failed to do better than ca. 5 kyu
>> because principles were only marginally better than 50%. Today, (my)
>> average principles discard the weaker, 50% principles and are ca. 75%.
>> Tomorrow, the 75% principles can be discarded for an average of 95%
>> principles. Expert systems get their chance again! Their major disadvantage
>> remains: great manpower is required for implementation. The advantage is
>> semantical understanding.
>>
>> --
>> robert jasiek
>>
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>
>
> 

Re: [Computer-go] AlphaGo Zero SGF - Free Use or Copyright?

[Jim O'Flaherty]

David Ongaro and Xavier Combelle,

I am respectfully requesting you stop inappropriately discussing and
addressing the person Robert Jasiek in your posts. He has not acted in any
way inappropriate on this list (I fully read every post). Therefore he
hasn't done anything which needs to be addressed regarding his
participation. However, each of you are acting inappropriately. Neither of
you are the final arbiter of what is valuable and/or appropriate for dialog
on this forum. And each of you has wandered into the space of inappropriate
discussion of a contributor here.

I enjoy Robert's posts. All of them. Yes, that includes the ones about
which each of you are complaining. Just because you do not value them
doesn't mean I don't value them. And, I also know there are others who ALSO
value Robert's posts. All of them.

As was said in an earlier reply, your email has a simple filtering
function. If you do not like a particular person's posts to this email
list, simply add their email to your list of blocked/ignored so it goes to
your spam or trash buckets and you never see it. IOW, please take
responsibility for your character and behavior and refrain from posting
non-Go related diatribes ESPECIALLY about other participating members.


Respectfully,

Jim O'Flaherty


On Tue, Oct 24, 2017 at 5:42 AM, <david.ong...@hamburg.de> wrote:

> On 2017-10-23 at 23:56, Thomas Rohde <t...@bonobo.com> wrote:
>
> > On 2017-10-23 at 19:15, Xavier Combelle <xavier.combe...@gmail.com>
> wrote:
> >
> > > Hi Robert Jasiek,
> > >
> > > you might have a delusional way to see the game of go and life,
> >
> > this is quite an insult
>
> Do you consider Robert's style of discussion "kind"? I for my part do not.
>
> I'm not saying that Robert's research in the area of Go corner cases
> doesn't have any value, it certainly has. One probably needs a certain kind
> of dedication to do it. But trying to bend every topic into this area is
> more often than not uncalled for.
>
> I don't know what it is. Maybe it's a certain kind of arrogance, resulting
> from the fact of knowing more than anybody else about a certain area in Go.
> But in the end it doesn't matter what it is, we all have our faults. What
> matters is that I very seldom saw a discussion with Robert lead to anything.
>
> David
>
>
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Re: [Computer-go] AlphaGo Zero SGF - Free Use or Copyright?

[Jim O'Flaherty]

If you wanted to do research on a specific joseki to see if AG0 found
weaknesses or explored alternatives, especially in games past day 3 (when
it began besting AGM), it would be quite interesting to see, through that
explicit filter, what kinds of things emerged around that specific joseki.
You might even discover that the joseki has weaknesses in several early
branches which haven't been found by humans in hundreds of years of using
the joseki.

Another angle is pretty much every game from AG0 day 4 forward would be
superior to the 100,000 games of the pro players upon which AGM was
trained. IOW, that is a huge number of games that exceed the very best
human-vs-human games quality and would be quite superior to seeding with
those human (biased) games for any other engine playing in the area.

Or, someone training a net, could walk up the 29 million games and explore
how their engine differs, make adjustments and explore climbing higher.
This data set enables "higher" in a totally different way than any prior
data set.

The number and variety of things that could be explored with the 29 million
games boggles the mind. I am deeply hopeful they do some form of simple
compressed dump of it somewhere. Then, it would be just a matter of getting
it loaded into a DB to create all sorts of indexes, queries, novel subsets,
etc.


Namaste,

Jim O'Flaherty
Founder/CEO
Precision Location Intelligence, Inc.
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On Mon, Oct 23, 2017 at 9:44 AM, Petri Pitkanen <petri.t.pitka...@gmail.com>
wrote:

> If the AG got better by playing against itself rather than training on
> previous good players then I do not thing training data is that important.
> Perhaps it is but google has shown that actually u dont need it. Just loads
> of processing will do the trick.
>
>
>
> 2017-10-23 15:05 GMT+03:00 Jim O'Flaherty <jim.oflaherty...@gmail.com>:
>
>> Couldn't they be useful as part of a set of training data for newly
>> trained engines and networks?
>>
>> On Oct 23, 2017 2:34 AM, "Petri Pitkanen" <petri.t.pitka...@gmail.com>
>> wrote:
>>
>>> They are free to use in any attribution. Game score is a reflection of
>>> historical fact and hence not copyrightable. Dunno what use them are to
>>> anyone though.
>>>
>>> Petri
>>>
>>> 2017-10-23 2:29 GMT+03:00 Lucas Baker <suuj...@gmail.com>:
>>>
>>>> Hi Robert,
>>>>
>>>> The AlphaGo Zero games are free to use with proper attribution, so
>>>> please use them as you like for commentaries as long as you credit 
>>>> DeepMind.
>>>>
>>>> Best,
>>>> Lucas Baker
>>>>
>>>> On Sun, Oct 22, 2017 at 3:59 PM Robert Jasiek <jas...@snafu.de> wrote:
>>>>
>>>>> AlphaGo Zero games are available as zipped SGF from Deepmind at
>>>>> http://www.alphago-games.com/ For earlier AlphaGo games, I have seen
>>>>> statements from Deepmind encouraging free use (presuming stating
>>>>> origin,
>>>>> of course) so that the games may be commented etc. I cannot find a
>>>>> similar statement from Deepmind for the published AlphaGo Zero games.
>>>>> Are they for free use or copyrighted? I hope the former so everybody
>>>>> including Deepmind can see more commentaries.
>>>>>
>>>>> --
>>>>> robert jasiek
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Re: [Computer-go] AlphaGo Zero SGF - Free Use or Copyright?

[Jim O'Flaherty]

Couldn't they be useful as part of a set of training data for newly trained
engines and networks?

On Oct 23, 2017 2:34 AM, "Petri Pitkanen" 
wrote:

> They are free to use in any attribution. Game score is a reflection of
> historical fact and hence not copyrightable. Dunno what use them are to
> anyone though.
>
> Petri
>
> 2017-10-23 2:29 GMT+03:00 Lucas Baker :
>
>> Hi Robert,
>>
>> The AlphaGo Zero games are free to use with proper attribution, so please
>> use them as you like for commentaries as long as you credit DeepMind.
>>
>> Best,
>> Lucas Baker
>>
>> On Sun, Oct 22, 2017 at 3:59 PM Robert Jasiek  wrote:
>>
>>> AlphaGo Zero games are available as zipped SGF from Deepmind at
>>> http://www.alphago-games.com/ For earlier AlphaGo games, I have seen
>>> statements from Deepmind encouraging free use (presuming stating origin,
>>> of course) so that the games may be commented etc. I cannot find a
>>> similar statement from Deepmind for the published AlphaGo Zero games.
>>> Are they for free use or copyrighted? I hope the former so everybody
>>> including Deepmind can see more commentaries.
>>>
>>> --
>>> robert jasiek
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Re: [Computer-go] What was the final score after the counting of AlphaGo-vs-Ke Jie Game #1?

[Jim O'Flaherty]

I have now heard that AlphaGo one by 0.5 points.


On Tue, May 23, 2017 at 2:00 AM, Jim O'Flaherty <jim.oflaherty...@gmail.com>
wrote:

> The announcer didn't have her mic on, so I couldn't hear the final score
> announced...
>
> So, what was the final score after the counting of AlphaGo-vs-Ke Jie Game
> #1?
>
>
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[Computer-go] What was the final score after the counting of AlphaGo-vs-Ke Jie Game #1?

[Jim O'Flaherty]

The announcer didn't have her mic on, so I couldn't hear the final score
announced...

So, what was the final score after the counting of AlphaGo-vs-Ke Jie Game
#1?
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Re: [Computer-go] Patterns and bad shape

[Jim O'Flaherty]

Now, I love this idea. A super fast cheap pattern matcher can act as input
into a neural network input layer in sort of a "pay additional attention
here and here and...".

On Apr 18, 2017 6:31 AM, "Brian Sheppard via Computer-go" <
computer-go@computer-go.org> wrote:

Adding patterns is very cheap: encode the patterns as an if/else tree, and
it is O(log n) to match.



Pattern matching as such did not show up as a significant component of
Pebbles. But that is mostly because all of the machinery that makes
pattern-matching cheap (incremental updating of 3x3 neighborhoods, and
related tricks) was a large component.



But I think that is the basic idea: pre-compute or incrementally compute
some basic functions of the board position so that pattern matching is
cheap. Then add as many patterns as possible.





*From:* Computer-go [mailto:computer-go-boun...@computer-go.org] *On Behalf
Of *Jim O'Flaherty
*Sent:* Monday, April 17, 2017 7:05 AM
*To:* computer-go@computer-go.org
*Subject:* Re: [Computer-go] Patterns and bad shape



It seems chasing down good moves for bad shapes would be an explosion of
"exception cases", like combinatorially huge. So, while you would be saving
some branching in the search space, you would be ballooning up the number
of patterns for which to scan by orders of magnitude.



Wouldn't it be preferable to just have the AI continue to make the better
move emergently and generally from probabilities around win placements as
opposed to what appears to be a focus on one type of local optima?





On Mon, Apr 17, 2017 at 5:07 AM, lemonsqueeze <lemonsque...@free.fr> wrote:

Hi,

I'm sure the topic must have come up before but i can't seem to find it
right now, i'd appreciate if someone can point me in the right direction.

I'm looking into MM, LFR and similar cpu-based pattern approaches for
generating priors, and was wondering about basic bad shape:

Let's say we use 6d games for training. The system becomes pretty good at
predicting 6d moves by learning patterns associated with the kind of moves
6d players make.

However it seems it doesn't learn to punish basic mistakes effectively (say
double ataris, shapes with obvious defects ...) because they almost never
show up in 6d games =) They show up in the search tree though and without
good answer search might take a long time to realize these moves don't work.

Maybe I missed some later paper / development but basically,
Wouldn't it make sense to also train on good answers to bad moves ?
(maybe harvesting them from the search tree or something like that)

I'm thinking about basic situations like this which patterns should be able
to recognize:

   A B C D E F G H J K L M N O P Q R S T
 +---+
  19 | . . . . . . . . . . . . . . . . . . . |
  18 | . . . O O . O . . . . . . . . . . . . |
  17 | . . X . X O . X O . . . . . . . . . . |
  16 | . . X . X O . O O . . . . . . X . . . |
  15 | . . . . . X X X X . . . . . . . . . . |
  14 | . . X . . . . . . . . . . . . . . . . |
  13 | . O . . . . . . . . . . . . X . O . . |
  12 | . . O . . . . . . . . . . . . . O . . |
  11 | . . O X . . . . . . . . . . . X . . . |
  10 | . . O X . . . . . . . . . . . X O . . |
   9 | . . O X . . . X . . . X O . . X O . . |
   8 | . . O X . . . O X X X O X)X X O O . . |
   7 | . O X . . . . . O O X O . X O O . . . |
   6 | O X X . X X X O . . O . . . X O X . . |
   5 | . O O . . O X . . . . . O . . . . . . |
   4 | . X O O O O X . . . O . . O . O . . . |
   3 | . X X X X O . . X . X X . . . . . . . |
   2 | . . . . X O . . . . . . O . . . . . . |
   1 | . . . . . . . . . . . . . . . . . . . |
 +---+

Patterns probably never see this during training and miss W L9,
For example :

In Remi's CrazyPatterns.exe L9 comes in 4th position:
   [ M10 N10 O6 L9 ...

With Pachi's large patterns it's 8th:
   [ G8  M10 G9  O17 N10 O6  J4  L9  ...

Cheers,
Matt



MM: Computing Elo Ratings of Move Patterns in the Game of Go
   https://www.remi-coulom.fr/Amsterdam2007/

LFR: Move Prediction in Go – Modelling Feature Interactions Using
  Latent Factors
   https://www.ismll.uni-hildesheim.de/pub/pdfs/wistuba_et_al_KI_2013.pdf


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Re: [Computer-go] Patterns and bad shape

[Jim O'Flaherty]

It seems chasing down good moves for bad shapes would be an explosion of
"exception cases", like combinatorially huge. So, while you would be saving
some branching in the search space, you would be ballooning up the number
of patterns for which to scan by orders of magnitude.

Wouldn't it be preferable to just have the AI continue to make the better
move emergently and generally from probabilities around win placements as
opposed to what appears to be a focus on one type of local optima?


On Mon, Apr 17, 2017 at 5:07 AM, lemonsqueeze  wrote:

> Hi,
>
> I'm sure the topic must have come up before but i can't seem to find it
> right now, i'd appreciate if someone can point me in the right direction.
>
> I'm looking into MM, LFR and similar cpu-based pattern approaches for
> generating priors, and was wondering about basic bad shape:
>
> Let's say we use 6d games for training. The system becomes pretty good at
> predicting 6d moves by learning patterns associated with the kind of moves
> 6d players make.
>
> However it seems it doesn't learn to punish basic mistakes effectively
> (say double ataris, shapes with obvious defects ...) because they almost
> never show up in 6d games =) They show up in the search tree though and
> without good answer search might take a long time to realize these moves
> don't work.
>
> Maybe I missed some later paper / development but basically,
> Wouldn't it make sense to also train on good answers to bad moves ?
> (maybe harvesting them from the search tree or something like that)
>
> I'm thinking about basic situations like this which patterns should be
> able to recognize:
>
>A B C D E F G H J K L M N O P Q R S T
>  +---+
>   19 | . . . . . . . . . . . . . . . . . . . |
>   18 | . . . O O . O . . . . . . . . . . . . |
>   17 | . . X . X O . X O . . . . . . . . . . |
>   16 | . . X . X O . O O . . . . . . X . . . |
>   15 | . . . . . X X X X . . . . . . . . . . |
>   14 | . . X . . . . . . . . . . . . . . . . |
>   13 | . O . . . . . . . . . . . . X . O . . |
>   12 | . . O . . . . . . . . . . . . . O . . |
>   11 | . . O X . . . . . . . . . . . X . . . |
>   10 | . . O X . . . . . . . . . . . X O . . |
>9 | . . O X . . . X . . . X O . . X O . . |
>8 | . . O X . . . O X X X O X)X X O O . . |
>7 | . O X . . . . . O O X O . X O O . . . |
>6 | O X X . X X X O . . O . . . X O X . . |
>5 | . O O . . O X . . . . . O . . . . . . |
>4 | . X O O O O X . . . O . . O . O . . . |
>3 | . X X X X O . . X . X X . . . . . . . |
>2 | . . . . X O . . . . . . O . . . . . . |
>1 | . . . . . . . . . . . . . . . . . . . |
>  +---+
>
> Patterns probably never see this during training and miss W L9,
> For example :
>
> In Remi's CrazyPatterns.exe L9 comes in 4th position:
>[ M10 N10 O6 L9 ...
>
> With Pachi's large patterns it's 8th:
>[ G8  M10 G9  O17 N10 O6  J4  L9  ...
>
> Cheers,
> Matt
>
> 
>
> MM: Computing Elo Ratings of Move Patterns in the Game of Go
>https://www.remi-coulom.fr/Amsterdam2007/
>
> LFR: Move Prediction in Go – Modelling Feature Interactions Using
>   Latent Factors
>https://www.ismll.uni-hildesheim.de/pub/pdfs/wistuba_et_al_KI_2013.pdf
>
>
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[Computer-go] AlphaGo returns in May...

[Jim O'Flaherty]

Looks like AlphaGo is returning in May (next month):

http://www.wired.co.uk/article/deepmind-go-alphago-china-may-2017
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Re: [Computer-go] dealing with multiple local optima

[Jim O'Flaherty]

NEAT and hyperNEAT are awesome when "evolving" fairly simple networks with
a very limited number of input and output dimensions. However, without
access to some serious computational power, scaling the NEAT method up to
the kind of level you would need for the current encoding methods for the
input layer used by AlphaGo into its ANNs and then the decoding methods for
the output layer, is likely not feasible for anything less than a Google
sized team and investment; i.e half a dozen people and millions of dollars
of computational access on their Google Cloud distributed computing
architecture. Amazon (with AWS) and Microsoft (with Azure) are the only two
other companies that would have the excess capacity in both supporting the
personnel and the distributed computation costs. A distant second would be
companies like IBM who could carry the personnel while leveraging AWS,
Azure, Google Cloud, etc.

Once there is a sufficient investment in this kind of evolutionary
meta-modeling, it will be a very useful starting point for others. However,
until someone is willing to play extremely long term and pony up the HUGE
up front costs of evolutionary bootstrapping out of the simple models NEAT
handles today, it is a short-term dead in.



On Fri, Feb 24, 2017 at 2:39 AM, Minjae Kim  wrote:

> I've recently viewed the paper of AlphaGo, which has done gradient-based
> reinforcement learning to get stronger. The learning was successful enough
> to beat a human master, but in this case, supervised learning with a large
> database of master level human games was preceded the reinforcement
> learning. For a complex enough game as go, one can expect that the search
> space for the policy function would not be smooth at all. So supposedly
> supervised learning was necessary to guide the policy function to a good
> starting point before reinforcement. Without such, applying reinforcement
> learning directly to a random policy can easily make the policy stuck at a
> bad local optimum. I could have a miunderstanding at this point; correct me
> if so, but to continue on: if it is hard to have "the good starting point"
> such as a trained policy from human expert game records, what is a way to
> devise one. I've had a look on NEAT and HyperNEAT, which are evolutionary
> methods. Do these evolutionary algorithms scale well on complex strategic
> decision processes and not just on simple linear decisions such as food
> gathering and danger avoidance? In case not, what alternatives are known?
> Is there any success case of a chess, go, or any kind of complex strategic
> game playing algorithm, where it gained expert strength without domain
> knowledge such as expert game examples?
>
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Re: [Computer-go] Notes from the Asilomar Conference on Beneficial AI

[Jim O'Flaherty]

I like your perspective, Adrian. It is more inline with the fractal nature
of knowledge itself. And the idea that computers might be able to
computationally explore deeper iterations in the fractal space than are
currently possible within human neural cognition is quite exciting.


On Fri, Feb 10, 2017 at 5:56 AM,  wrote:

> Richard J Lorentz  writes:
>
> > Thanks for the interesting link. Indeed, some good reading there.
> >
> > One quote that I've seen various versions of a number of times now: "
> > More interesting for the rest of us, AlphaGo is playing moves and
> > styles that all human masters had dismissed as stupid centuries ago."
>
> Related to this, the idea was mentioned that maybe AlphaGo is
> beating humans partially because the strategies employed have
> gotten trapped in a local minimum due to historical factors.
>
> It might not necessarily be historical factors, but simply that
> the techniques that AlphaGo has been finding are just too hard
> for humans to learn or use effectively.  For example, in
> mathematics, different techniques have been developed for both
> symbolic and numerical manipulation for use in computer programs,
> but humans don't use these because they are tedious or difficult
> to error check, place a heavy load on memory, or don't provide
> intuitive insight.  Likewise, it could be that certain strategies
> work well in Go but require keeping track of details and playing
> out more precisely than human abilities typically allow.
>
> It is nice to hope that we could learn something about Go from
> AlphaGo, but we may learn little more than what mathematicians
> learn when a computer-assisted proof consisting of several
> hundred pages is generated for a conjecture like Fermat's last
> theorem.
>
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Re: [Computer-go] Are the AlphaGols coming?

[Jim O'Flaherty]

David, that's a fantastic and succinct summarization. Tysvm!


On Jan 9, 2017 12:19 AM, "David Ongaro"  wrote:

> On Jan 5, 2017, at 10:49 PM, Robert Jasiek  wrote:
>
>
> On 06.01.2017 03:36, David Ongaro wrote:
>
> Two amateur players where analyzing a Game and a professional player
> happened to come by.
> So they asked him how he would assess the position. After a quick look he
> said “White is
>
> > leading by two points”. The two players where wondering: “You can count
> that quickly?”
>
> Usually, accurate positional judgement (not only territory but all
> aspects) takes between a few seconds and 3 minutes, depending on the
> position and provided one is familiar with the theory.
>
>
> Believe it or not, you also rely on “feelings” otherwise you wouldn’t be
> able to survive.
>
> Some see DNNs as some kind of “cache” which has knowledge of the world in
> compressed form. Because it's compressed it can’t always reproduce learned
> facts with absolute accuracy but on the other hand it has the much more
> desired feature to even yield reasonable results for states it never saw
> before.
>
> Mathematically (the approach you seem yourself constrain into) there
> doesn’t seem to be a good reason why this should work. But if you take the
> physical structure of the world into account things change. In fact there
> is a recent pretty interesting paper (not only for you, but surely also for
> other readers in this list) about this topic: https://arxiv.org/abs/
> 1608.08225.
>
> I interpret the paper like this: the number of states we have to be
> prepared for with our neural networks (either electronic or biological) may
> be huge, but compared to all mathematically possible states it's almost
> nothing. That is due to the fact that our observable universe is an
> emergent result of relatively simple physical laws. That is also the reason
> why deep networks (i.e. with many layers) work so well, even though
> mathematically a one layer network is enough. If the emergent behaviours of
> our universe can be understand in layers of abstractions, we can scale our
> network linearly by the number of layers matching the number of
> abstractions. That’s a huge win over the exponential growth required when
> we need a mathematical correct solution for all possible states.
>
> The “physical laws” for Go are also relatively simple and the complexity
> of Go is an emergent result of these. That is also the reason why the DNNs
> are trained with real Go positions not just with random positions, which
> make up the majority of all possible Go positions. Does that mean the DNNs
> won’t perform well when evaluating random positions, or even just the
> "arcane positions” you discussed with Jim? Absolutely! But it doesn’t have
> to. That’s not its flaw but its genius.
>
> David O.
>
>
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Re: [Computer-go] Our Silicon Overlord

[Jim O'Flaherty]

I love your dedication to the principles of logic. I'm looking forward to
hearing and seeing how your explorations in this area pan out. They will be
valuable to everyone interested in exploring AI weaknesses. I hope you get
access to AlphaGo ASAP.

On Jan 6, 2017 11:28 PM, "Robert Jasiek" <jas...@snafu.de> wrote:

> On 06.01.2017 23:37, Jim O'Flaherty wrote:
>
>> into a position with superko [...] how do you even get AlphaGo into a the
>> arcane
>> state in the first place,
>>
>
> I can't in practice.
>
> I have not provided a way to beat AlphaGo from the game start at the empty
> board.
>
> All I have shown is that there are positions beyond AlphaGo's capabilities
> to refute your claim that AlphaGo would handle all positions well.
>
> Hui and Lee constructed positions with such aspects: Hui with long-term
> aji, Lee with complex reduction aji. Some versions of AlphaGo mishandled
> the situations locally or locally + globally.
>
> The professional players will be
>> open to all sorts of creative ideas on how to find weaknesses with
>> AlphaGo.
>>
>
> Or the amateur players or theoreticians.
>
> Perhaps you can persuade one of the 9p-s to explore your idea
>> of pushing the AlphaGo AI in this direction.
>>
>
> Rather I'd need playing time against AlphaGo.
>
> IOW, we are now well outside of provable spaces
>>
>
> For certain given positions, proofs of difficulty exist. Since Go is a
> complete-information game, there can never be a proof that AlphaGo could
> never do it. There can only ever be proofs of difficulty.
>
> mathematical proof around a full game
>>
>
> From the empty board? Of course not (today).
>
> We cannot formally prove much simpler models,
>>
>
> Formal proofs for certain types of positions (such as with round_up(n/2)
> n-tuple kos) exist.
>
> --
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Re: [Computer-go] Our Silicon Overlord

[Jim O'Flaherty]

Okay. So I will play along. How do you think you would coax AlphaGo into a
position with superko without AlphaGo having already simulated that pathway
as a less probable win space for itself when compared to other playing
trees which avoid it? IOW, how do you even get AlphaGo into a the arcane
state in the first place, especially since uncertainty of outcome is
weighted against wins for itself?

And since I know you cannot definitively answer that, it looks like we'll
just have to wait and see what happens. The professional players will be
open to all sorts of creative ideas on how to find weaknesses with AlphaGo.
And until they get free reign to play as many games as they like against it
so they can begin to get a feel for strategies that do expose probable
weaknesses (we won't know with certainty as it appears AlphaGo is now
generating its own theories where a situation is rated a weakness by a
human turns out to be incorrect and AlphaGo ends up leveraging it to its
advantage). Perhaps you can persuade one of the 9p-s to explore your idea
of pushing the AlphaGo AI in this direction.

IOW, we are now well outside of provable spaces and into probabilistic
spaces. At the scales we are discussing, it is improbable we will ever
directly experience seeing anything approaching a mathematical proof around
a full game of Go between two experts, even if those experts are two
competing AIs. We cannot formally prove much simpler models, much less ones
with the complexity of a game of Go.


On Fri, Jan 6, 2017 at 12:55 AM, Robert Jasiek <jas...@snafu.de> wrote:

> On 05.01.2017 17:32, Jim O'Flaherty wrote:
>
>> I don't follow.
>>
>
> 1) "For each arcane position reached, there would now be ample data for
> AlphaGo to train on that particular pathway." is false. See below.
>
> 2) "two strategies. The first would be to avoid the state in the first
> place." Does AlphaGo have any strategy ever? If it does, does it have
> strategies of avoiding certain types of positions?
>
> 3) "the second would be to optimize play in that particular state." If you
> mean optimise play = maximise winning probability.
>
> But... optimising this is hard when (under positional superko) optimal
> play can be ca. 13,500,000 moves long and the tree to that is huge. Even
> TPU sampling can be lost then.
>
> Afterwards, there is still only one position from which to train. For NN
> learning, one position is not enough and cannot replace analysis by
> mathematical proofs ALA the NN does not emulate mathematical proving.
>
>
> --
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Re: [Computer-go] Are the AlphaGols coming?

[Jim O'Flaherty]

That was a quite elegant way to present the idea. Ty for sharing.

On Jan 5, 2017 8:36 PM, "David Ongaro"  wrote:

> This discussion reminds me of an incident which happened at the EGC in
> Tuchola 2004 (maybe someone can find a source for this). I don’t remember
> all details but it was about like this:
>
> Two amateur players where analyzing a Game and a professional player
> happened to come by. So they asked him how he would assess the position.
> After a quick look he said “White is leading by two points”. The two
> players where wondering: “You can count that quickly?”, but the pro
> answered “No, I just asked myself if I would like to have black in this
> position. The answer is no. But with two extra Komi for Black it would feel
> ok.”
>
> So it seems professionals already acquired some kind of “value network”
> due to their hard training, but they also can modify its assessments by
> taking Komi into account. Maybe that's something we also should do, i.e.
> not only train the value network by taking go positions and results into
> account but also add the Komi as an input (the output would still be a
> simple win/lose result). In that way we don’t have to train a different
> network for each Komi, even though the problem getting enough training data
> for all Komi values still remains.
>
>
> On Jan 5, 2017, at 11:44 AM, David Ongaro  wrote:
>
>
> On Jan 5, 2017, at 2:37 AM, Detlef Schmicker  wrote:
>
> Hi,
>
> what makes you think the opening theory with reverse komi would be the
> same as with standard komi?
>
> I would be afraid to invest an enormous amount of time just to learn,
> that you have to open differently in reverse komi games :)
>
>
> Thats why I used the comparative adjective “less”. It might not be ideal,
> but still much better than changing the fundamental structure of the
> opening with an extra stone. Furthermore the effect might not as big as you
> think:
>
> 1. The stronger player doesn’t have to play overplays when the handicap is
> correct. If the handicap is correct and if AlphaGo “knows” that is another
> question though… Of course the weaker player might play differently (i.e.
> more safely) but at least that is something he or she can control
> 2. One could even argue the other way around:  we might see more sound
> (theoretically correct) moves from AlphaGo with reverse Komi. If it's
> seeing itself ahead already during the opening it might resort to slack but
> safe moves. Since it’s still winning we can be left wondering if it was
> actually a good move. But if it does an unusual looking move which it can’t
> be considered an overplay but it’s still winning in the end with reverse
> Komi there should be a real insight to gain.
>
> Still, a reverse Komi handicap is rather big, but it might be the next
> best thing we have without retraining the value network from scratch.
> Furthermore retraining the value network will probably affect the playing
> style even more.
>
> Thanks,
>
> David O.
>
>
> Am 05.01.2017 um 10:50 schrieb Paweł Morawiecki:
>
> 2017-01-04 21:07 GMT+01:00 David Ongaro :
>
>
> [...]So my question is: is it possible to have reverse Komi games
> by feeding the value network with reverse colors?
>
>
> In the paper from Nature (subsection "Features for policy/value
> network"), authors state:
>
> *the stone colour at each intersection was represented as either
> player or opponent rather than black or white. *
>
> Then, I think the AlphaGo algorithm would be fine with a reverse
> komi. Namely, a human player takes black and has 7.5 komi. The next
> step is that AlphaGo gives 2 stones of handicap but keeps 7.5 komi
> (normally you have 0.5).
>
> Aja, can you confirm this?
>
>
> Also having 2 stone games is not so interesting since it would
> reveal less insights for even game opening Theory.
>
>
> I agree with David here, most insights we would get from even
> games. But we can imagine the following show. Some games are played
> with a reverse komi, some games would be played with 2 stones (yet,
> white keeps 7.5 komi) and eventually the main event with normal
> even games to debunk our myths on the game. Wouldn't be super
> exciting!?
>
> Best regards, Paweł
>
>
>
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Re: [Computer-go] Our Silicon Overlord

[Jim O'Flaherty]

For each arcane position reached, there would now be ample data for AlphaGo
to train on that particular pathway. And it would emerge two strategies.
The first would be to avoid the state in the first place. And the second
would be to optimize play in that particular state. So, the human advantage
would be very short lived.

On Thu, Jan 5, 2017 at 12:37 AM, Robert Jasiek  wrote:

> On 04.01.2017 22:08, "Ingo Althöfer" wrote:
>
>> humanity's last hope
>>
>
> The "last hope" are theoreticians creating arcane positions far outside
> the NN of AlphaGo so that its deep reading would be insufficient
> compensation! Another chance is long-term, subtle creation and use of aji.
>
> --
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>
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Re: [Computer-go] Are the AlphaGols coming?

[Jim O'Flaherty]

Tysvm for posting that!

I had predicted it was AlphaGo from the beginning. If there is a competitor
emerging, I think we would have seen some sort of publicity around it, if
not just to provoke a response with the AlphaGo team.


On Wed, Jan 4, 2017 at 9:11 AM, Janzert  wrote:

> On 1/2/2017 7:05 AM, "Ingo Althöfer" wrote:
>
>> Hello Paweł,
>>
>> There have been another 8 games on Foxwq server:
>>> ...
>>> Totally, 38-0. It looks like a kind, indirect (yet powerful), message
>>> from DeepMind to Chinese Go Association: "Please, let us try a real
>>> challenge, like 3-handicap games, it does not really make much sense
>>> to play even anymore".
>>>
>>
>> So, do you want to say that "Master" might be AlphaGo?
>> From the disucssion I thought that "Master" was a chinese bot.
>>
>> If Aja is reading: can you enlighten us?
>>
>> Cheers, Ingo.
>>
>
> Looks like we have an official answer in the affirmative
> https://twitter.com/demishassabis/status/816660463282954240
>
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Re: [Computer-go] Poll: Scientific Breakthrough of the Year 2016

[Jim O'Flaherty]

Using Windows 10 and Chrome, I voted successfully. I also posted a link to
it on Facebook.


On Wed, Nov 30, 2016 at 11:21 AM, Michael Alford  wrote:

> I've tried Firefox and Safari on Mac, and Firefox and Chrome on Debian. I
> have used the link and accessed the page from the main page.  In all
> instances the Submit is grayed out and does not function.
>
>
> Michael
>
>
>
>
> On 11/30/16 6:06 AM, "Ingo Althöfer" wrote:
>
>> Hi,
>> I just learned that the magazine "Science" is making a poll
>> on "Scientific Breakthrough of the Year 2016". Voters may
>> chose amongst 15 proposals. Voting closes on December 04.
>>
>> Currently the following 5 subjects have top votes.
>>
>> (1) Human embryos in a disc  17 %
>> (2) Ripples in space time  15 %
>> (3) AI in games (AlphaGo) 9 %
>> (4) Pocket sized DNA sequencers  8 %
>> (5) Custom designed proteins  7 %
>>
>> http://www.sciencemag.org/news/2016/11/vote-your-scientific-
>> breakthrough-year
>>
>> Feel free to participate.
>> No registration needed.
>>
>> Ingo.
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Re: [Computer-go] computergo.org domain

[Jim O'Flaherty]

Are you implying this email list will stop functioning if this domain isn't
renewed?

On Tue, Sep 27, 2016 at 12:07 AM, Joshua Shriver  wrote:

> My domain expires in 6 days, so heads up it's free to grab if anyone wants
> it.
>
> -Josh
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Re: [Computer-go] Video of Aja Huang's presentation

[Jim O'Flaherty]

Awesome! Tysvm!

On Thu, Jul 7, 2016 at 8:03 AM, Igor Polyakov <weiqiprogramm...@gmail.com>
wrote:

> Here it is:
>
> https://youtu.be/KoIv7oYZ8wc
>
> On 2016-07-06 12:03, Jim O'Flaherty wrote:
>
> Any chance someone has put this on Youtube for those of us who primarily
> consume videos on phones or tablets (where a 2.0GB is very large to store
> locally)? And if so, replying with a link here would be deeply appreciated.
>
>
> On Wed, Jul 6, 2016 at 10:38 AM, "Ingo Althöfer" <3-hirn-ver...@gmx.de>
> wrote:
>
>> now online at:
>> http://liacs.leidenuniv.nl/~csicga/cg2016/ah1.mov
>>
>> Ingo.
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Re: [Computer-go] Video of Aja Huang's presentation

[Jim O'Flaherty]

Any chance someone has put this on Youtube for those of us who primarily
consume videos on phones or tablets (where a 2.0GB is very large to store
locally)? And if so, replying with a link here would be deeply appreciated.


On Wed, Jul 6, 2016 at 10:38 AM, "Ingo Althöfer" <3-hirn-ver...@gmx.de>
wrote:

> now online at:
> http://liacs.leidenuniv.nl/~csicga/cg2016/ah1.mov
>
> Ingo.
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Re: [Computer-go] Keynote Lecture by Aja Huang

[Jim O'Flaherty]

I enthusiastically second that!
On Jun 16, 2016 1:15 PM, "David Fotland"  wrote:

> Can the lecture be recorded or broadcast for those of us who can’t be
> there?
>
> Regards,
>
> David
>
> > -Original Message-
> > From: Computer-go [mailto:computer-go-boun...@computer-go.org] On
> > Behalf Of "Ingo Althöfer"
> > Sent: Thursday, June 16, 2016 9:36 AM
> > To: computer-go@computer-go.org
> > Subject: [Computer-go] Keynote Lecture by Aja Huang
> >
> > Hello,
> >
> > the ICGA is proud to annouce a special talk by Aja Huang during the
> > Computer Olympiad and "Computer Games" conference in Leiden (NL).
> >
> >  Computer and Games 2016 Conference 
> >
> > Keynote Lecture
> > June 29, 2016: 14.00-15.00 h.
> >
> > Location: Leiden University, room 1 of the Gorlaeus Building
> >
> > Lecture by Aja Huang of the AlphaGo team
> >
> > AlphaGo: Combining Deep Neural Networks with Tree Search
> >
> > Abstract
> > In this talk we will present the source of power of AlphaGo. In
> > AlphaGo, we use  value networks  to evaluate board positions and
> > policy networks  to select moves. These deep neural networks are
> > trained by a novel combination of supervised learning from human expert
> > games, and reinforcement learning from games of self-play. Without any
> > look ahead search, the neural networks play Go at the level of state-
> > of-the-art Monte Carlo tree search programs that simulate thousands of
> > random games of self-play. We also introduce a new search algorithm
> > that combines Monte Carlo simulation with value and policy networks.
> > Using this search algorithm, our program AlphaGo achieved a 99.8%
> > winning rate against other Go programs, and defeated the human European
> > Go champion by 5 games to 0. In March 2016 AlphaGo defeated Lee Sedol,
> > the strongest human Go player in the last decade.
> > 
> >
> > Hope, you all will come.
> >
> > Cheers, Ingo.
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Re: [Computer-go] Creating the playout NN

[Jim O'Flaherty]

BTW, by improvement, I don't mean higher Go playing skill...I mean
appearing close to the same level of Go playing skill _per_ _move_ with far
less computational cost. It's the total game outcomes that will fall.

On Sun, Jun 12, 2016 at 3:55 PM, Jim O'Flaherty <jim.oflaherty...@gmail.com>
wrote:

> The purpose is to see if there is some sort of "simplification" available
> to the emerged complex functions encoded in the weights. It is a typical
> reductionist strategy, especially where there is an attempt to converge on
> human conceptualization. Given the complexity of the nuances in Go, my
> intuition says that it will show excellent improvement in short term play
> at the cost of nuance in longer term play.
>
> On Sun, Jun 12, 2016 at 6:05 AM, Álvaro Begué <alvaro.be...@gmail.com>
> wrote:
>
>> I don't understand the point of using the deeper network to train the
>> shallower one. If you had enough data to be able to train a model with many
>> parameters, you have enough to train a model with fewer parameters.
>>
>> Álvaro.
>>
>>
>> On Sun, Jun 12, 2016 at 5:52 AM, Michael Markefka <
>> michael.marke...@gmail.com> wrote:
>>
>>> Might be worthwhile to try the faster, shallower policy network as a
>>> MCTS replacement if it were fast enough to support enough breadth.
>>> Could cut down on some of the scoring variations that confuse rather
>>> than inform the score expectation.
>>>
>>> On Sun, Jun 12, 2016 at 10:56 AM, Stefan Kaitschick
>>> <skaitsch...@gmail.com> wrote:
>>> > I don't know how the added training compares to direct training of the
>>> > shallow network.
>>> > It's prob. not so important, because both should be much faster than
>>> the
>>> > training of the deep NN.
>>> > Accuracy should be slightly improved.
>>> >
>>> > Together, that might not justify the effort. But I think the fact that
>>> you
>>> > can create the mimicking NN, after the deep NN has been refined with
>>> self
>>> > play, is important.
>>> >
>>> > On Sun, Jun 12, 2016 at 9:51 AM, Petri Pitkanen <
>>> petri.t.pitka...@gmail.com>
>>> > wrote:
>>> >>
>>> >> Would the expected improvement be reduced training time or improved
>>> >> accuracy?
>>> >>
>>> >>
>>> >> 2016-06-11 23:06 GMT+03:00 Stefan Kaitschick
>>> >> <stefan.kaitsch...@hamburg.de>:
>>> >>>
>>> >>> If I understood it right, the playout NN in AlphaGo was created by
>>> using
>>> >>> the same training set as the one used for the large NN that is used
>>> in the
>>> >>> tree. There would be an alternative though. I don't know if this is
>>> the best
>>> >>> source, but here is one example: https://arxiv.org/pdf/1312.6184.pdf
>>> >>> The idea is to teach a shallow NN to mimic the outputs of a deeper
>>> net.
>>> >>> For one thing, this seems to give better results than direct
>>> training on the
>>> >>> same set. But also, more importantly, this could be done after the
>>> large NN
>>> >>> has been improved with selfplay.
>>> >>> And after that, the selfplay could be restarted with the new playout
>>> NN.
>>> >>> So it seems to me, there is real room for improvement here.
>>> >>>
>>> >>> Stefan
>>> >>>
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>>> >>
>>> >>
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Re: [Computer-go] Creating the playout NN

[Jim O'Flaherty]

The purpose is to see if there is some sort of "simplification" available
to the emerged complex functions encoded in the weights. It is a typical
reductionist strategy, especially where there is an attempt to converge on
human conceptualization. Given the complexity of the nuances in Go, my
intuition says that it will show excellent improvement in short term play
at the cost of nuance in longer term play.

On Sun, Jun 12, 2016 at 6:05 AM, Álvaro Begué 
wrote:

> I don't understand the point of using the deeper network to train the
> shallower one. If you had enough data to be able to train a model with many
> parameters, you have enough to train a model with fewer parameters.
>
> Álvaro.
>
>
> On Sun, Jun 12, 2016 at 5:52 AM, Michael Markefka <
> michael.marke...@gmail.com> wrote:
>
>> Might be worthwhile to try the faster, shallower policy network as a
>> MCTS replacement if it were fast enough to support enough breadth.
>> Could cut down on some of the scoring variations that confuse rather
>> than inform the score expectation.
>>
>> On Sun, Jun 12, 2016 at 10:56 AM, Stefan Kaitschick
>>  wrote:
>> > I don't know how the added training compares to direct training of the
>> > shallow network.
>> > It's prob. not so important, because both should be much faster than the
>> > training of the deep NN.
>> > Accuracy should be slightly improved.
>> >
>> > Together, that might not justify the effort. But I think the fact that
>> you
>> > can create the mimicking NN, after the deep NN has been refined with
>> self
>> > play, is important.
>> >
>> > On Sun, Jun 12, 2016 at 9:51 AM, Petri Pitkanen <
>> petri.t.pitka...@gmail.com>
>> > wrote:
>> >>
>> >> Would the expected improvement be reduced training time or improved
>> >> accuracy?
>> >>
>> >>
>> >> 2016-06-11 23:06 GMT+03:00 Stefan Kaitschick
>> >> :
>> >>>
>> >>> If I understood it right, the playout NN in AlphaGo was created by
>> using
>> >>> the same training set as the one used for the large NN that is used
>> in the
>> >>> tree. There would be an alternative though. I don't know if this is
>> the best
>> >>> source, but here is one example: https://arxiv.org/pdf/1312.6184.pdf
>> >>> The idea is to teach a shallow NN to mimic the outputs of a deeper
>> net.
>> >>> For one thing, this seems to give better results than direct training
>> on the
>> >>> same set. But also, more importantly, this could be done after the
>> large NN
>> >>> has been improved with selfplay.
>> >>> And after that, the selfplay could be restarted with the new playout
>> NN.
>> >>> So it seems to me, there is real room for improvement here.
>> >>>
>> >>> Stefan
>> >>>
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>> >>
>> >>
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Re: [Computer-go] GRS

[Jim O'Flaherty]

Have you considered using either of the two high level Go AIs (mentioned on
this email group this last week) as your end-of-game live-group estimator
(and could even use their scoring mechanism, too)?


On Sun, Jun 12, 2016 at 8:02 AM, Henry Hemming  wrote:

> Unfortunately I had to make some changes to
> http://goratingserver.appspot.com , which broke the bot interface
> (updates now come in via web sockets). However it should now be a lot
> easier to connect a bot to the server as I created a jar file and
> configuration ini file that connects a command line gtp bot to the server
> just like on KGS. The jar file and an example ini file (for gnu-go) as well
> as source code is available at https://github.com/typohh/GTPRest .
>
> Hopefully the site looks prettier and works more reliably now. Dead stone
> estimation should be much more accurate and only need cleanup in
> exceptional circumstances (fewer than than 1/200 games). I have no
> intention of putting up ads on the site and only plan to charge for custom
> names nothing else (to cover some of the server costs). Because of the
> changes in protocol the official launch of the website also got delayed, if
> however everything runs smoothly for a few more days I will run two day
> tournament for beta testers to stress test the site followed by a public
> tournament (basically whoever gets highest rating before deadline, and
> another category with additional minimum number of games played during the
> tournament time frame). Bots will be welcome to participate in the
> tournament, more on that later.
>
> Right now there are some human beta testers and 4 bots playing on the
> site. The bots are between 15kyu, and 2dan which should guarantee a pairing
> for any player within ~15 minutes at most.
>
> Once again any and all feedback much appreciated.
>
> -Henry Hemming
>
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Re: [Computer-go] AlphaGo to play against Ke Jie

[Jim O'Flaherty]

Until it comes officially from Demis Hassabis, it's a rumor to drive
traffic to the "leak" announcer.
On Jun 10, 2016 9:25 AM, "Falk Heuer"  wrote:

> According to China Daily from 31.5, they are probably playing in October.
> http://europe.chinadaily.com.cn/business/2016-05/31/content_25554898.htm
>
> Falk
>
>
> On 2016-06-04 20:00, "Ingo Althöfer" wrote:
>
> Hi,
>
> during the amateur World Championships in Wuxi
> the new president of the international Go Association,
> Yang Jun'an, announced that Chinese young star Ke Jie
> will play against AlphaGo.
>
> No fixed date was announced, yet.
> Does someone here know more details?
>
> Ingo.
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>
> 
>  Virenfrei.
> www.avast.com
> 
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Re: [Computer-go] AlphaGo to play against Ke Jie

[Jim O'Flaherty]

This is SO exciting.
On Jun 4, 2016 10:01 PM, Ingo Althöfer <3-hirn-ver...@gmx.de> wrote:

> Hi,
>
> during the amateur World Championships in Wuxi
> the new president of the international Go Association,
> Yang Jun'an, announced that Chinese young star Ke Jie
> will play against AlphaGo.
>
> No fixed date was announced, yet.
> Does someone here know more details?
>
> Ingo.
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Re: [Computer-go] Leela 0.6.2, OpenCL support, including GTP engines

[Jim O'Flaherty]

This is wonderful, both the engine and the UI. And the fact the engine is
available alone, is awesome! Tysvm!


On Sat, Jun 4, 2016 at 6:20 PM, Gian-Carlo Pascutto  wrote:

> Hi all,
>
> I've done a major update of Leela, including integration of DCNN, and
> optional usage of OpenCL to speed things up via the GPU.
>
> https://sjeng.org/leela.html
>
> I put a GTP commandline executable on the page. I hope the other people
> developing engines find this useful - I found the dearth of suitable
> testing opponents a bit of a hindrance.
>
> There are binaries for Windows, Windows+OpenCL and Linux-x64. Static
> linking with OpenCL didn't work on the first attempt, so no Linux+OpenCL
> for now.
>
> --
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Re: [Computer-go] Crazystone on Steam

[Jim O'Flaherty]

Tysvm! The video on Stream is a very nice touch. And the first review rocks!

On Fri, May 27, 2016 at 1:36 PM, Andreas Persson  wrote:

> Congrats on the Steam release of Crazystone Rémi! Hope it will sell well.
> For people that haven't seen it here is a link
> http://store.steampowered.com/app/479330/. Bit to pricey for me but will
> pick it up at some point, enjoy the ios app a lot.
>
> /Andreas
>
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Re: [Computer-go] May KGS bot tournament

[Jim O'Flaherty]

Hmmm...if bots weaker than GnuGo are actively discouraged, perhaps there
could be a separate tournament level for that grouping of "aspiring
computer Go" entrants (if it isn't too much extra work). Having bots earn
the right to move into the higher level of (i.e. have met the entry
requirement of "consistently beats GnuGo version X.Y) might be a nice
filter as the number of those desiring to participate (with weaker bots)
rises.

On Wed, May 4, 2016 at 4:01 AM, Urban Hafner 
wrote:

> I’m considering entering with my bot but it’s rather weak (a lot weaker
> than GnuGo on 19x19) so I don’t know if it makes sense. Unless of course
> other weaker bots were willing to enter as well. If no one is interested in
> this (or if it’s even discouraged by Nick) then I would refrain from
> entering tournaments that I have no chance in beating GnuGo.
>
> Urban
>
> On Mon, May 2, 2016 at 6:51 PM, Nick Wedd  wrote:
>
>> The May KGS bot tournament will start on Sunday, May 8th at 16:00 UTC,
>> and finish by 22:00 UTC.  It will use 19x19 boards, with time limits of
>> 14 minutes each plus very fast Canadian overtime, and komi of 7.5. See
>> http://www.gokgs.com/tournEntrants.jsp?id=1030
>>
>> Please register by emailing me, with the words "KGS Tournament Registration"
>> in the email title, at mapr...@gmail.com .
>>
>> Nick
>> --
>> Nick Wedd  mapr...@gmail.com
>>
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Re: [Computer-go] Is Go group pattern recognition by CNN possible?

[Jim O'Flaherty]

Petr,

Tysvm! I really appreciate that.


Jim


On Thu, Apr 21, 2016 at 4:41 AM, Josef Moudrik  wrote:

> Thank you!
>
> Dne čt 21. 4. 2016 11:17 uživatel Petr Baudis  napsal:
>
>>   Hi!
>>
>>   Since "the record's stuck", I have found this as another rant without
>> point, and djhbrown hasn't responded to my private request for staying
>> on topic and friendly, I have taken the liberty to "cast the first
>> stone" and
>>
>> enabled the moderation bit for djhbrown.
>>
>>   I'll be happy to pass through any mail that could have an interesting
>> insight, otherwise I invite those enjoying these reads to watch his
>> blog and youtube channel.
>>
>> On Thu, Apr 21, 2016 at 11:52:01AM +1000, djhbrown . wrote:
>> > Surely, someone, somewhere, has used, or tried to use, a CNN to label
>> > groups in a Go game 361-pixellation?
>> >
>> > Q: what's the point of Go?
>> > A: 361
>> >
>> > (you would have thought someone else would have already thought of that
>> one)
>> >
>> > Minsky and Papert threw a spanner into the works of the NN Magi of the
>> > day, but whose grandchildren are now basking in the reflected glow of
>> > their triumphal triumphant  Man Who Would be King Apollo
>> > Al(pha)exander who has conquered further far East than Kaffiristan -
>> > Peace Be Upon Her prophet Kipling.
>> >
>> > The spanner was that the MPs found out that Perceptrons were Baron
>> > Munchausen Walter Mittys who couldn't see the hole in a doughnut,
>> > which meant that although they could learn to out-Pong space invaders,
>> > they would become lost in a Pacman maze.  As they did, as Dm hirelings
>> > let slip out of the bag.
>> >
>> > Later, or before, depending on how you look at it, Backpropagators
>> > claimed to have overcome this clog in their Jaquard's Loom in a Simple
>> > Twist of Fate by claiming that Minsky was ancient history just as he
>> > had claimed that they would so become [1], and now the new religion of
>> > Stratified Convolutionism is claiming columnar accession to the throne
>> > of AI, after Marchly breaking the back of the monster Orwellian
>> > Goldstein gold standard Enemy of the Statespace, so it's just a few
>> > weeks left to the Singularity, say the homeopathic snake-oil homology
>> > self-promotional entrepreneurial salesmen.
>> >
>> > Sir Humphrey: "Everything is connected... who said that?"
>> > Bernard: "The Cabinet Secretary?"
>> > Sir H: "Nearly right; actually, it was Lenin"
>> >
>> > Norman Mailer once ranted that critics should be shot, but The Prince
>> > Vespasian Flavius was cunninger, seeing the wisdom of his
>> > Machiavelli-of-the-day Josephus that rather than claim to be the Sun
>> > incarnate (as had his predecessors and as would his son's successors)
>> > and attempt ViViVi by enfilade brute force, he could rule over the
>> > southern desert troublemakers more easily and cheaply by spin
>> > propaganda alone, simply by pretending he and his son Titus were the
>> > earthly allegory of the heavenly born-again Messiah they yearned for
>> > and put into that character's mouth the platitude that they should
>> > render unto Caesar what is Caesar's, and love their enemies rather
>> > than stone them.
>> >
>> > And it worked, for two thousand years, and is still going strong
>> > despite a few seminal whacky  leaks, just as Monty Python's Black
>> > Adder Baldrick C(u)NN(ing) Plan has created a Reich that will last a
>> > thousand years and upon which the sun will never set, so let us parrot
>> > Hymn Number google in the Good Bok of Not the Nine O-Clock News [2]
>> > and that other one:
>> >
>> >  "it (symbolic reasoning) is an ex-parrot; it has ceased to be.  Monty
>> > is Great!  I avow that there is no Go but Monty.".
>> >
>> > Apologies to those unfamiliar with the various historical allusions
>> > that are variously common and uncommon knowledge among readers of A
>> > History of the English-Speaking Peoples, to whom it will be somewhat
>> > illusory without Googling the Gogglebox. which may cause the more
>> > insecure among them to jump on the bandwagon of striking the first
>> > blow and casting the first stone for the umpteenth time, anxious for
>> > attention and the comfort blanket of communal hatred of any straw man
>> > that stumbles across their blinkered monochrome landscape, so to
>> > relieve the burden of thought, Sherpa the Sean suggests somewheres to
>> > start:
>> >
>> > 1. http://www.webofstories.com/play/marvin.minsky/25
>> >
>> > 2. https://www.youtube.com/watch?v=kqilW8OpeGc
>> >
>> > Only a Dostoyevskian Idiot-ic lone wolf apostate would dare leave the
>> > quiet safety of the silent steppes to risk the monotonic ugly-mouthed
>> > egg-throwing of self-righteous smug lion camp followers snug in their
>> > schooled mutual hatred of anything or anyone with more melanin or a
>> > different perspective than their straightjacket mindset.
>> >
>> > The record's stuck, the record's stuck.
>> > 

Re: [Computer-go] OmegaGo

[Jim O'Flaherty]

The td;lr I got from his "treatise" was "be cautious investing in mimicking
AlphaGo's success, or you will be electrocuted by some Jacob fella"

djhbrown's been doing pretty well recently staying related and relevant to
the subject area. This is the first time in awhile he's wandered this far
off into his kind of free association space again. I sense he's looking to
be useful and taking stabs at being so. Everyone desires to be respected
and admired. Some people want it a bit more aggressively than others, and
some even more especially as they enter the latter stages of life.


On Wed, Apr 20, 2016 at 2:12 PM, uurtamo .  wrote:

> Pamphlets <= treatises
> On Apr 20, 2016 11:17 AM, "David Ongaro"  wrote:
>
>> Some of "Dr. Browns" pamphlets remind me of Herman Hesse's Steppenwolf.
>> But Hesse's text was much more refined and enjoyable to read, so I think
>> "SPAM" is a fitting categorisation.
>>
>>
>>
>> > On 20 Apr 2016, at 00:57, Michael Markefka 
>> wrote:
>> >
>> > Can I flag this as spam?
>> >
>> > On Tue, Apr 19, 2016 at 11:23 PM, djhbrown . 
>> wrote:
>> >> 6D out of the blue is no mean achievement,...  60+ years ago, the
>> >> market for gizmos in UK was flooded with cheap Japanese copies of
>> >> European products; but whilst innovation and product quality
>> >> improvement by European manufacturers faded as their fat cat owners
>> >> complacently went cocacola-soaked soft,  Japanese industry, unlike its
>> >> USA counterpart, was listening attentively to the wise words of
>> >> W.Edwards Deming (eg [1,2]) and beginning to improve the reliability,
>> >> efficiency and efficacy of its products, and by about 30 years ago,
>> >> Japanese engineering was the equal or better of even German
>> >> technology.
>> >>
>> >> Korean, Formosan and Hong Kong e-tigers followed hotfoot in Japan's
>> >> footsteps, and now the same thing is happening in China, so we can
>> >> expect to see a vast array of Shanghai-teenager-bedroom-produced
>> >> shanghaied miniclones of Alpha, most with unimaginative copycat names
>> >> like Beta, Eta, Theta, AIota etc, skulking around the corridors of the
>> >> Internet, all of which will at first be cheap imitations, but sowing
>> >> the seeds of in-house and inter-house R quality circles, so that
>> >> their own descendants will before very long become to Californian IT
>> >> as Japanese fuel-efficient reliable engines are to US unreliable
>> >> gas-guzzlers.
>> >>
>> >> Watch out Google Cloud byte-guzzlers, teenage rebels with the lessons
>> >> of Deming in their notebooks, who have learned from history and from
>> >> the sterling modus operandi of Steve Jobs and Uncle Tom Cobley et al,
>> >> are on their way up your Jacob's ladder...
>> >>
>> >> 1.  Charles A. Barclay (1993) Quality Strategy and TQM Policies:
>> >> Empirical Evidence.
>> >> MIR: Management International Review Vol. 33, Strategic Quality
>> Management.
>> >> 2.
>> http://asq.org/learn-about-quality/total-quality-management/overview/deming-points.html
>> >>
>>  Anybody knows who is the author of BetaGo? It is playing with account
>>  GoBeta on KGS, and is 6d.
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Re: [Computer-go] Beginner question : how to choose a board representation

[Jim O'Flaherty]

What programming language and OS environment have you chosen?
On Apr 10, 2016 2:19 AM, "Jean-Francois Romang"  wrote:

> Hello to everyone ; I'm a newcomer in this list and computer go
> programming. I have a chess programming background, but I want to start
> something new. :-)
> I'm currently in the early phases of developing GTP compatible go engine ;
> now it's time for me to choose a board representation : are there some
> articles or tips on this ?
> Thanks,
> Jean-Francois
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Re: [Computer-go] "English Explanations" based on Neural Networks

[Jim O'Flaherty]

Petr,

You know, just exploring this conversation is motivating to me, even if I
am still seeing it as huge risk with small payoff.

I like your line of thinking in that from a top down approach, we start
simple and just push it as far as it can go, acknowledging we won't likely
get anywhere near the kind of depth and meaning Robert Jasiek has in his
joseki works. IOW, the goal is to make some sort of "topical" progress from
the top down as even a small amount here would have some value and an
impact on some percentage of human players. The balance would be to spend a
small amount to get a small payoff just to begin to sound out where the
threshold of diminishing returns might be on the top down approach.


Jim


On Thu, Mar 31, 2016 at 12:21 PM, Petr Baudis <pa...@ucw.cz> wrote:

> On Thu, Mar 31, 2016 at 08:51:30AM -0500, Jim O'Flaherty wrote:
> > What I was addressing was more around what Robert Jasiek is describing in
> > his joseki books and other materials he's produced. And it is exactly
> why I
> > think the "explanation of the suggested moves" requires a much deeper
> > baking into the participating ANN's (bottom up approach). And given what
> I
> > have read thus far (including your above information), I am still seeing
> > the risk extraordinarily high and the payoff exceedingly low, outside an
> > academic context.
>
>   I think we may just have a different outcome in mind.  To illustrate
> where I think my approach could work, that could be for example
> (slightly edited):
>
> > White Q5 was played to compel Black to extend at the bottom.
> > If Black doesn’t respond, White’s pincer at K4 will be powerful.
>
> in
> https://gogameguru.com/lee-sedol-defeats-alphago-masterful-comeback-game-4/
>
>
>   Sure, it seems a bit outrageous, and for initial attempts, generating
> utterances like
>
> > White 126 was a very big move which helped to ensure White’s advantage.
>
> is perhaps more realistic (though many of these sentences are a bit
> of truisms and not terribly informative).  But I'm quite convinced that
> even the first example is completely plausible.
>
>   (But I'm *not* talking about generating pages of diagrams that
> describe an opening position in detail.  That's to ponder when we
> get the simpler things right.)
>
> --
> Petr Baudis
> If you have good ideas, good data and fast computers,
> you can do almost anything. -- Geoffrey Hinton
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Re: [Computer-go] new challenge for Go programmers

[Jim O'Flaherty]

Ingo,

That's precisely what has my knickers in a twist regarding djhbrown; his
prior behavior. I'm with you in that I hope that he better manages his
participation and uses list feedback to spend a little more time filtering
what his "creativity" so it fits closer to the listening of this specific
audience. Thus far, with some minor exceptions, he's been substantially
better this time.


Jim


On Thu, Mar 31, 2016 at 3:30 AM, "Ingo Althöfer" <3-hirn-ver...@gmx.de>
wrote:

> Hello all,
>
> "Brian Sheppard"  wrote:
> > ... This is out of line, IMO. Djhbrown asked a sensible question that has
> > valuable intentions. I would like to see responsible, thoughtful, and
> > constructive replies.
>
> there is a natural explanation why some people here react allergic
> to Djhbrown's new contributions.
>
> He had an active phase on the list already from early August 2015 to mid
> October. Things started interestingly, but somehow he went into a
> "strange loop", and in the end he was asked to stop posting.
> http://computer-go.org/pipermail/computer-go/2015-October/008051.html
>
> Perhaps all sides can help that things run better now.
>
> Ingo.
>
> PS. For my interest in computer-assisted human go
> visualisation questions on DCNNs are indeed interesting.
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Re: [Computer-go] new challenge for Go programmers

[Jim O'Flaherty]

Robert,

This is exactly why I think the "explanation of the suggested moves"
requires a much deeper baking into the participating ANN's (bottom up
approach). And given what I have read thus far, I am still seeing the risk
extraordinarily high and the payoff exceedingly low, outside an academic
context.

However, if someone was to do all the dirty work setting up all the
infrastructure, hunt down the training data and then financially facilitate
the thousands of hours of human work and the tens to hundreds of thousands
of hours of automated learning work, I would become substantially more
interested...and think a high quality desired outcome remains a low
probability.


Jim


On Thu, Mar 31, 2016 at 7:33 AM, Robert Jasiek  wrote:

> On 31.03.2016 13:43, Bill Whig wrote:
>
>> Joseki learning requires much more than move suggestions.
>>>
>> Prove it.
>>
>
> Read my four joseki books and my two books on positional judgement for a
> proof. Hints: global context, evaluation, strategic choices, tactical
> reading, many strategic concepts etc. All these are required for good human
> joseki play and (far) beyond move suggestions.
>
> --
> robert jasiek
>
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Re: [Computer-go] new challenge for Go programmers

[Jim O'Flaherty]

I don't think djhbrown is a software engineer. And he seems to have the
most fits. :)

On Wed, Mar 30, 2016 at 6:37 PM, uurtamo .  wrote:

> This is clearly the alphago final laugh; make an email list responder to
> send programmers into fits.
>
> s.
> On Mar 30, 2016 4:16 PM, "djhbrown ."  wrote:
>
>> thank you very much Ben for sharing the inception work, which may well
>> open the door to a new avenue of AI research.  i am particularly
>> impressed by one pithy statement the authors make:
>>
>>  "We must go deeper: Iterations"
>>
>> i remember as an undergrad being impressed by the expressive power of
>> recursive functions, and later by the iterative quality of biological
>> growth and its fractal nature.
>>
>> seeing animals in clouds is a bit like seeing geta in a go position;
>> so maybe one way to approach the problem of chatting with a CNN might
>> be to seek correlations between convolution weights and successive
>> stone configurations that turn up time and time again in games.
>>
>> it may be that some kind of iterative procedure could do this, just as
>> my iterative procedure for circumscribing a group has a recursive
>> quality to its definition.
>>
>> all you need then is to give such a correlation a name, and you will
>> be on the way to discovering a new language for talking about Go.
>>
>>
>> On 31/03/2016, Ben  wrote:
>> > It would be very interesting to see what these go playing neural
>> > networks dream about [1].
>> > [1]
>> >
>> http://googleresearch.blogspot.de/2015/06/inceptionism-going-deeper-into-neural.html
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Re: [Computer-go] new challenge for Go programmers

[Jim O'Flaherty]

I agree, "cannot" is too strong. But, values close enough to "extremely
difficult as to be unlikely" is why I used it.
On Mar 30, 2016 11:12 AM, "Robert Jasiek" <jas...@snafu.de> wrote:

> On 30.03.2016 16:58, Jim O'Flaherty wrote:
>
>> My own study says that we cannot top down include "English explanations"
>> of
>> how the ANNs (Artificial Neural Networks, of which DCNN is just one type)
>> arrive a conclusions.
>>
>
> "cannot" is a strong word. I would use it only if it were proven
> mathematically.
>
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Re: [Computer-go] new challenge for Go programmers

[Jim O'Flaherty]

My own study says that we cannot top down include "English explanations" of
how the ANNs (Artificial Neural Networks, of which DCNN is just one type)
arrive a conclusions. If you want to translate the computational value of
an ANN into something other than the essential operation that it is
performing, that computational value has to be "grown" into the ANN at the
same time the original computational value is being "reinforced learning
baked in". And when doing that, it costs considerably in both computational
energy and in the extra amount of time the growing of the ANN to produce
the integrated "suggest a move and then offer human meaningful English
explanations for the suggestion". And this assumes English as the language
and a single move suggestion. Add another human language and/or make it
suggest more than one move, and you explode the resources required to
converge on a solution that would eventually beat an amateur, much less a
professional.

Consider ANNs from an entirely different place; our own wetware. Our
wet-ware doesn't learn English and attach explanations to most of its
cognitive activities. And to those activities to which it does attach
English explanations, we have discovered that it is very prone to blind
spots and severe biases that turn into feedback loops magnifying the size
of the blind spots and the degree of biasing. So, even evolution didn't
spend the time to give us a mechanism that can self-describe all or even
most of its operation. And introspection, what we do have that allows us to
self-evaluate is very error prone (apologies to all egos that just got very
activated by being publicly outed as less capable than they know they
actually are).

Another way to consider this is to find out what has happened in the Chess
world with similar desired effects. While they have not been using ANNs
near as strongly, they still have the same desire effects to produce
"English explanations" for move suggestions. I think you will find, even in
this vastly simpler computational space, they haven't made much progress in
this area, either. In otherwords, it is proving to be highly expensive for
insufficient payoff; i.e. an evolutionary dead end.

You say, "Unfortunately no one has a clue on how to put into words what
DCNN "know", to produce really meaningful and useful feedback, justifying
decisions around candidates, etc. This is very much worth investigating."

I have a clue. However, for me personally, I find the investment required
to do said investigation to be WAY too high compared to the actual value
yield I _might_ _eventually_ get from the investment. There is far more low
hanging fruit in the Go AI and ANN space that I could choose (and am
choosing) before I would choose something so highly speculative your
investigation.


On Wed, Mar 30, 2016 at 7:49 AM, djhbrown .  wrote:

> I fully agree with Goncalo that it would be worth investigating how
> one could write an algorithm to express in English what Alpha's or
> DCNNigo's nets
> have learned, and a month ago (before her astonishing achievement in
> March) offerred some ideas on how this might be approached in a
> youtube comment on Kim's review of the Fan Hui games:
> https://www.youtube.com/watch?v=NHRHUHW6HQE
>
> the relevant section of which is (abridged):
>
> "a further, "higher-level" pattern leaning algorithm might be able to
> induce correlation and/or implication relationships between
> convolutions, enabling it to begin to develop its own ontology of
> perceptions, perhaps by correlating convolution relationships with
> geometric patterns on the board image. ... i look forward to the day
> when someone can find a way to induce symbolic pattern descriptions of
> relationships between convolutions and image patterns so that betago
> (child of alpha) can explain its "thinking" in a way we can understand
> and perhaps learn from too."
>
> On 30/03/2016, Gonçalo Mendes Ferreira  wrote:
> > Come on let's all calm down please. :)
> >
> > David I think the great challenge is in having good insight with AlphaGo
> > strength. Many Faces already provides some textual move suggestions, as
> > do probably other programs. Any program that doesn't use exclusively
> > machine learning or global search, like GNU Go, should be able to
> > suggest how it came about a move.
> >
> > Unfortunately no one has a clue on how to put into words what DCNN
> > "know", to produce really meaningful and useful feedback, justifying
> > decisions around candidates, etc. This is very much worth investigating.
> >
> > - Gonçalo
> >
> >
> >
> > On 30/03/2016 12:32, Álvaro Begué wrote:
> >>> no lack of respect for DeepMind's achievement was contained in my
> >>> posting; on the contrary, i was as surprised as anyone at how well she
> >>> did and it gave me great pause for thought.
> >>>
> >>
> >> Well, you wrote this:
> >>
> >>> but convolutional neural networks and monte-carlo simulators have not
> >>> advanced the 

Re: [Computer-go] *****SPAM***** Re: UEC cup 2nd day

[Jim O'Flaherty]

Which one is Remi's?

On Thu, Mar 24, 2016 at 1:09 AM, David Fotland 
wrote:

> There was one program (Shrike) that had a dnn without search.  It didn’t
> finish in the top 8.  Zen and Crazystone have custom DNN implementations.
> Dark Forest uses Torch.  The rest used Caffe.
>
> Remi's implementation is unusual and interesting.  I'll let him share it
> if he wants to.
>
> David
>
> > -Original Message-
> > From: Computer-go [mailto:computer-go-boun...@computer-go.org] On
> Behalf Of
> > Darren Cook
> > Sent: Wednesday, March 23, 2016 5:19 AM
> > To: computer-go@computer-go.org
> > Subject: *SPAM* Re: [Computer-go] UEC cup 2nd day
> >
> > David Fotland wrote:
> > > There are 12 programs here that have deep neural nets.  2 were not
> > > qualified for the second day, and six of them made the final 8.  Many
> > > Faces has very basic DNN support, but it s turned off because it isn t
> > > making the program stronger yet.  Only Dolburam and Many Faces don t
> > > have DNN in the final 8.  Dolburam won in Beijing, but the DNN
> > > programs are stronger and it didn t make the final 4.
> >
> > Are all the DNN programs (or, at least, all 6 in the top 8) also using
> MCTS?
> > (Re-phrased: is there any currently strong program not using MCTS?)
> >
> > Darren
> > ___
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Re: [Computer-go] Congratulations to AlphaGo (Statistical significance of results)

[Jim O'Flaherty]

I think you are reinforcing Simon's original point; i.e. using a more fine
grained approach to statically approximate AlphaGo's ELO where fine grained
is degree of vetting per move and/or a series of moves. That is a
substantially larger sample size and each sample will have a pretty high
degree of quality (given the vetting is being done by top level
professionals).
On Mar 22, 2016 1:04 PM, "Jeffrey Greenberg"  wrote:

> Given the minimal sample size, bothering over this question won't amount
> to much. I think the proper response is that no one thought we'd see this
> level of play at this point in our AI efforts and point to the fact that we
> witnessed hundreds of moves vetted by 9dan players, especially Michael
> Redmond's, where each move was vetted. In other words "was the level of
> play very high?" versus the question "have we beat all humans". The answer
> is more or less, yes.
>
> On Tuesday, March 22, 2016, Lucas, Simon M  wrote:
>
>> Hi all,
>>
>> I was discussing the results with a colleague outside
>> of the Game AI area the other day when he raised
>> the question (which applies to nearly all sporting events,
>> given the small sample size involved)
>> of statistical significance - suggesting that on another week
>> the result might have been 4-1 to Lee Sedol.
>>
>> I pointed out that in games of skill there's much more to judge than just
>> the final
>> outcome of each game, but wondered if anyone had any better (or worse :)
>> arguments - or had even engaged in the same type of
>> conversation.
>>
>> With AlphaGo winning 4 games to 1, from a simplistic
>> stats point of view (with the prior assumption of a fair
>> coin toss) you'd not be able to claim much statistical
>> significance, yet most (me included) believe that
>> AlphaGo is a genuinely better Go player than Lee Sedol.
>>
>> From a stats viewpoint you can use this approach:
>> http://www.inference.phy.cam.ac.uk/itprnn/book.pdf
>> (see section 3.2 on page 51)
>>
>> but given even priors it won't tell you much.
>>
>> Anyone know any good references for refuting this
>> type of argument - the fact is of course that a game of Go
>> is nothing like a coin toss.  Games of skill tend to base their
>> outcomes on the result of many (in the case of Go many hundreds of)
>> individual actions.
>>
>> Best wishes,
>>
>>   Simon
>>
>>
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Re: [Computer-go] Go Bot for the Browser?

[Jim O'Flaherty]

This is wonderful! Tysvm for reposting!


On Thu, Mar 17, 2016 at 3:07 PM, Álvaro Begué 
wrote:

> A while back somebody posted a link to a browser implementation of a DCNN:
> https://chrisc36.github.io/deep-go/
>
> Would something like that do?
>
> Álvaro.
>
>
>
> On Wed, Mar 16, 2016 at 4:44 PM, Benjamin Teuber 
> wrote:
>
>> Hi everyone,
>>
>> for a Go beginner website I would like to have a bot that runs in
>> client-side javascript, it doesn't have to be that strong.
>> An option might be transpiling gnugo with emscripten, but I'm not very
>> familiar with that technology and the first google entry (
>> http://comments.gmane.org/gmane.comp.compilers.emscripten/1051) looks
>> like it might be not so easy.
>>
>> Any ideas? Or even better, is anyone curious about it and willing to
>> help? :)
>>
>> Regards Benjamin
>>
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Re: [Computer-go] computergo.org

[Jim O'Flaherty]

So I hear you volunteering to create and maintain that site/page? {smirk}
On Mar 19, 2016 6:40 AM, "Gonçalo Mendes Ferreira"  wrote:

> Instead of just redirecting, it could be a directory page for:
> - various Nick Wedd pages
> - CGOS
> - mailing lists
> - the game AI forum
> - news sites
> - aggregators of tournament information, ICGA
> - aggregator or list of upcoming conferences
> - links to software and tools
> - lists of publications, Martin Müller's page, etc
>
> Gonçalo
>
>
> On 19/03/2016 01:07, Joshua Shriver wrote:
> > Agree, main reason I snagged it was mostly to make sure it would be
> > used and not end up some spam or adult site.
> >
> > I do like the idea of re-directing and that could be done in minutes.
> > Which do you feel is better the host of this list, or the .info one?
> >
> > -Josh
> >
> > On Fri, Mar 18, 2016 at 4:58 PM, David Doshay  wrote:
> >> sorry about that auto-correct ‘typo. The first one is supposed to be
> computergo.org, but that should be clear anyway ...
> >>
> >> Cheers,
> >> David G Doshay
> >>
> >> ddos...@mac.com
> >>
> >>
> >>
> >>
> >>
> >>> On 18, Mar 2016, at 1:56 PM, David Doshay  wrote:
> >>>
> >>> From my perspective, having both a computer.org and a computer-go.org
> seems redundant.
> >>>
> >>> Cheers,
> >>> David G Doshay
> >>>
> >>> ddos...@mac.com
> >>>
> >>>
> >>>
> >>>
> >>>
>  On 18, Mar 2016, at 12:49 PM, Gonçalo Mendes Ferreira 
> wrote:
> 
>  I don't know how up-to-date computer-go.info is, but it appears a
> better
>  target for redirecting.
> 
>  - Gonçalo
> 
>  On 18/03/2016 19:46, Xavier Combelle wrote:
> > 2016-03-17 16:16 GMT+01:00 Joshua Shriver :
> >
> >> Does anyone have interest in that domain name? I'd be willing to
> >> transfer it to a new owner for free.  It came up a year or so back
> and
> >> I grabbed it just in case but never used it.
> >>
> >> Rather see it go to someone who can use it rather than squat. It's
> >> already for another year.
> >>
> >> -Josh
> >> ___
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> >> Computer-go@computer-go.org
> >> http://computer-go.org/mailman/listinfo/computer-go
> >
> >
> > I would vote for redirecting to computer-go.org if everybody agree
> (or the
> > other direction should be good too)
> >
> >
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Re: [Computer-go] AlphaGo & DCNN: Handling long-range dependency

[Jim O'Flaherty]

Whatever the case, a huge turn has been made and the next 5 years in Go are
going to be surprising and absolutely fascinating. For a game that +2,500
years old, I'm beyond euphoric to be alive to get to witness this.


On Mon, Mar 14, 2016 at 4:15 PM, Darren Cook  wrote:

> > You can also look at the score differentials. If the game is perfect,
> > then the game ends up on 7 points every time. If players made one
> > small error (2 points), then the distribution would be much narrower
> > than it is.
>
> I was with you up to this point, but players (computer and strong
> humans) play to win, not to maximize the score. So a small error in the
> opening or middle game can literally be worth anything by the time the
> game ends.
>
> > I am certain that there is a vast gap between humans and perfect
> > play. Maybe 24 points? Four stones??
>
> 24pts would be about two stones (if each handicap stone is twice komi,
> e.g. see http://senseis.xmp.net/?topic=2464).
>
> The old saying is that a pro would need to take 3 to 4 stones against
> god (i.e. perfect play).
>
> Darren
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Re: [Computer-go] AlphaGo & DCNN: Handling long-range dependency

[Jim O'Flaherty]

I'm using the term "teacher" loosely. Any player who is better than me is
an opportunity to learn. Being able to interact with the superior AI player
strictly through actual play in a repeatable and undo-able form allows me
to experiment and explore independently, in a way not achievable with a
superior skilled human. This doesn't diminish the value of human teachers.
In fact, I see them exploiting AIs to 'trivially play out all variations"
when attempting to demonstrate why a particular move is desirable or
undesirable.

To support your point, though, I completely agree the kind of formalization
you are pursuing will have even higher value as the AIs stretch out beyond
humans. I think your work when combined with an untiring AI assistant will
help human Go considerably. I know I have been helped greatly by your work,
and I'm at a very amateur skill level.

And your right about the more rigorous meaning of teacher (or Sensei) being
quite a bit further away. I'm hopeful other AI breakthroughs outside of the
Go domain will help close the gap more quickly.
On Mar 14, 2016 9:21 AM, "Robert Jasiek" <jas...@snafu.de> wrote:

> On 14.03.2016 08:59, Jim O'Flaherty wrote:
>
>> an AI player who becomes a better and better teacher.
>>
>
> But you are aware that becoming a stronger AI player does not equal
> becoming a stronger teacher? Teachers also need to (translate to and)
> convey human knowledge and reasoning, and adapt to the specific pupils'
> needs (incl. reasoning, subconscious thinking and psychology) while
> interacting with human language specialised in go language. Solve two dozen
> AI tasks, combine them and then, maybe, you get the equivalent of a
> teacher. [FYI, I have taught 100+ regular single go pupils since 2008, and
> groups of pupils.]
>
> --
> robert jasiek
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Re: [Computer-go] Congratulations to AlphaGo

[Jim O'Flaherty]

I'd expect this achievement by AlphaGo is very similar to when the first
human ran a 4 minute mile. No one had done it prior. However, right after
Roger Bannister did it, suddenly there were people all over the planet
doing it. Roger Bannister essentially made the possibility real, and then
the psychology changed and lots of others made it over the hurdle. AlphaGo
turned the possibility of an AI becoming a 9d into reality.

AlphaGo may have made it to 9d first. However, I expect we will now begin
seeing lots of different successful attempts to accomplish the same thing,
and relatively soon, too. We've already seen several different comments on
this email list of people working furiously to make the same leaps the
AlphaGo team have described creating. The risk on these investments has
been substantially reduced by AlphaGo's unambiguous success. If the chess
world is any sort of guide to how Go AI is going to continue to develop,
then we will see plenty of progress over the next 36 months. I wouldn't be
surprised to hear the Facebook team working on their AI ends up coming in
second to the +9d AI club.


On Sat, Mar 12, 2016 at 6:25 PM, Igor Polyakov 
wrote:

> At this point I don't doubt that the single machine version is
> professional strength which is enough to be used as a tool to analyze
> games...
>
>
> On 2016-03-12 16:24, Lukas van de Wiel wrote:
>
> This would be many thousands of dollars per day. A single game would be
> more than a thousand dollars in total costs.
> I do not think a kickstarter project or so would be successful, as the go
> community is simply not *that* big...
>
> On Sun, Mar 13, 2016 at 1:17 PM, Gonçalo Mendes Ferreira < 
> go...@sapo.pt> wrote:
>
>> It does seem unlikely for DeepMind not to move on to "bigger" things,
>> but maybe the Go community can make some kind of fundraiser to keep an
>> instance of AlphaGo playing 24/7? I think there are some websites for
>> this kind of thing. Someone would be in charge of scheduling time for it
>> to play pros, other programs, and maybe play online on breaks. Just an
>> idea, oh Google overlords that watch all communications.
>>
>> Gonçalo
>>
>> On 13/03/2016 00:06, Lukas van de Wiel wrote:
>> > Oh, I did not say that it would not be beneficial, to AlphaGo, and to
>> the
>> > people playing it, and to the Go community as a whole, but still, it
>> will
>> > have to come from somewhere. Just the electricity bill alone would be
>> > hair-raising.
>> > And the big-scale benefits in prestige and marketing are over, with this
>> > victory.
>> >
>> > It would be cool to build on the works of AlphaGo, and I would like to
>> see
>> > it as much as the next enthusiast, but I doubt the feasibility...
>> >
>> > On Sun, Mar 13, 2016 at 1:01 PM, Thomas Wolf < 
>> tw...@brocku.ca> wrote:
>> >
>> >>
>> >>
>> >> On Sat, 12 Mar 2016, Lukas van de Wiel wrote:
>> >>
>> >> And the hardware available for this tournament was tremendous. It
>> remains
>> >>> to be seen whether the hardware and the people
>> >>> maintaining it would be available for a longer period. The costs of
>> this
>> >>> are not to be underestimated. Who would pay it?
>> >>>
>> >>
>> >> The AlphaGo team would get feedback from testing by players with very
>> >> different ideas/strengths who they would otherwise never get in contact
>> >> with.
>> >>
>> >> For example, Michael Redmond mentioned repeatedly in the last 3 reviews
>> >> that
>> >> he would love to play AlphaGo to study Go, to find new openings,...
>> >>
>> >>
>> >>
>> >>> Lukas
>> >>>
>> >>> On Sun, Mar 13, 2016 at 12:20 PM, Clark B. Wierda > >
>> >>> wrote:
>> >>>   On Sat, Mar 12, 2016 at 5:05 PM, Thomas Wolf 
>> >>> wrote:
>> >>> Having AlphaGo playing exclusively on KGS would be such a
>> >>> boost to KGS!
>> >>>
>> >>>   For sure.
>> >>>
>> >>> The other Go servers might have their own opinion on that.
>> >>>
>> >>> Clark
>> >>>
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Re: [Computer-go] Congratulations to AlphaGo

[Jim O'Flaherty]

I think you're correct, Thomas. The challenge is going to be getting ANY
professional to be the one who "takes handicap stones" for the first time
in years. The possible "shame" of doing so is what will make it messy.

Once someone does take that step, though, I think it is only a matter of
time before the rating of humans will be made a subordinate rating relative
to the "objective" rating of the AIs, AlphaGo just being the first. And
that has its own psychological challenges as the Go world has many decades
of handling ELOs and rankings for humans. So, I don't think change in this
area is going to be welcomed anytime soon.


On Sat, Mar 12, 2016 at 3:03 PM, Thomas Wolf <tw...@brocku.ca> wrote:

> Chris,
>
> Prompted from a discussion on the computer go email list
> (and my last email today) :
>
> We currently have no measure at all to judge how safe a winor loss is at
> any
> stage of the game. The measure applied currently of counting territory does
> only apply if both players try to maximize territory but not if at least
> one
> player maximizes the chance of winning. (I know, it was mentioned already).
>
> But really, comments like "Player ... is catching up" are pretty
> meaningless
> and are only valid if one explicitly mentions points or territorry, and
> adds
> that this has nothing to do with winning probabilities.
>
> Even the winning percentages provided by the computer programs themselves
> are
> no real indicator for winninig chances. They are tools to find the best
> move
> and are a statistical measure over several playout sequences based on
> selfplay
> not based on play against that opponent. Equally, winning percentages
> worked
> out by other computer programs are also not adequate (although they are at
> least unbiased) because they do also not use the real opponents to play out
> the sequences.
>
> The only valid strength indicator would be to gradually increase handicap
> stones or komi for the previous loser in a series of games.
>
> Regards,
> Thomas
>
>
> On Sat, 12 Mar 2016, Sorin Gherman wrote:
>
>
>> It is fascinating indeed to try to find how much stronger is AlphaGo
>> compared to top humans.
>>
>> Given the fact that it is hard to find the reason why Lee Sedol lost, and
>> that AlphaGo seems to get mysteriously ahead without a clear reason, tells
>> me that the difference is definitely more than one stone handicap, maybe
>> 2+
>> stones, as crazy as it may sound given Lee Sedol's level.
>>
>> I am pretty sure he will not accept to play with handicap against AlphaGo
>> though. Maybe "younger wolves" like Ke Jie will though and we will find
>> out.
>>
>> On Mar 12, 2016 11:03 AM, "Thomas Wolf" <tw...@brocku.ca> wrote:
>>   A suggestion for possible future games to be arranged between
>>   AlphaGo and
>>   strong players:
>>
>>   Whoever lost shall be given 1 stone or the equivalent of 1/2
>>   stone handcap in the
>>   next game. Games should continue until each side has won at
>>   least once. This
>>   way AlphaGo will be forced to demonstrate its full strength over
>>   a whole game
>>   which we are all too curious to see.
>>
>>   Thomas
>>
>>   On Sat, 12 Mar 2016, Aja Huang wrote:
>>
>> Thanks all. AlphaGo has won the match against Lee
>> Sedol. But there are still 2 games to play.
>> Aja
>>
>> On Sat, Mar 12, 2016 at 5:49 PM, Jim O'Flaherty
>> <jim.oflaherty...@gmail.com> wrote:
>>   It was exhilerating to witness history being
>> made! Awesome!
>>
>> On Sat, Mar 12, 2016 at 2:17 AM, David Fotland
>> <fotl...@smart-games.com> wrote:
>>
>>   Tremendous games by AlphaGo.  Congratulations!
>>
>>
>>
>>   From: Computer-go
>> [mailto:computer-go-boun...@computer-go.org] On
>> Behalf Of Lukas van de Wiel
>>   Sent: Saturday, March 12, 2016 12:14 AM
>>   To: computer-go@computer-go.org
>>   Subject: [Computer-go] Congratulations to
>> AlphaGo
>>
>>
>>
>> Whoa, what a fight! Well fought, and well won!
>>
>> Lukas
>>
>>
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Re: [Computer-go] Congratulations to AlphaGo

[Jim O'Flaherty]

I LOVE this suggestion!


On Sat, Mar 12, 2016 at 1:02 PM, Thomas Wolf <tw...@brocku.ca> wrote:

> A suggestion for possible future games to be arranged between AlphaGo and
> strong players:
>
> Whoever lost shall be given 1 stone or the equivalent of 1/2 stone handcap
> in the
> next game. Games should continue until each side has won at least once.
> This
> way AlphaGo will be forced to demonstrate its full strength over a whole
> game
> which we are all too curious to see.
>
> Thomas
>
>
> On Sat, 12 Mar 2016, Aja Huang wrote:
>
> Thanks all. AlphaGo has won the match against Lee Sedol. But there are
>> still 2 games to play.
>> Aja
>>
>> On Sat, Mar 12, 2016 at 5:49 PM, Jim O'Flaherty <
>> jim.oflaherty...@gmail.com> wrote:
>>   It was exhilerating to witness history being made! Awesome!
>>
>> On Sat, Mar 12, 2016 at 2:17 AM, David Fotland <fotl...@smart-games.com>
>> wrote:
>>
>>   Tremendous games by AlphaGo.  Congratulations!
>>
>>
>>
>>   From: Computer-go [mailto:computer-go-boun...@computer-go.org] On
>> Behalf Of Lukas van de Wiel
>>   Sent: Saturday, March 12, 2016 12:14 AM
>>   To: computer-go@computer-go.org
>>   Subject: [Computer-go] Congratulations to AlphaGo
>>
>>
>>
>> Whoa, what a fight! Well fought, and well won!
>>
>> Lukas
>>
>>
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Re: [Computer-go] Congratulations to AlphaGo

[Jim O'Flaherty]

It was exhilerating to witness history being made! Awesome!

On Sat, Mar 12, 2016 at 2:17 AM, David Fotland 
wrote:

> Tremendous games by AlphaGo.  Congratulations!
>
>
>
> *From:* Computer-go [mailto:computer-go-boun...@computer-go.org] *On
> Behalf Of *Lukas van de Wiel
> *Sent:* Saturday, March 12, 2016 12:14 AM
> *To:* computer-go@computer-go.org
> *Subject:* [Computer-go] Congratulations to AlphaGo
>
>
>
> Whoa, what a fight! Well fought, and well won!
>
> Lukas
>
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Re: [Computer-go] Finding Alphago's Weaknesses

[Jim O'Flaherty]

I think we are going to see a case of human professionals having drifted
into a local optima in at least three areas:
  1) Early training around openings is so ingrained in their acquiring
their skill (optimal neural plasticity window), there has been very little
new discovery around the first third of the game with almost all
professionals relying fairly strongly on the already time tested josekis -
AIs can use reading to explore closer and closer to the start of a game
using less and less automatic patterns thereby confusing humans who have
memorized those patterns
  2) The middle of the board is so high in reading complexity, there has
been little investment to figure out how to leverage it until mid game as
it has been more expedient to focus on the corners and edges - AIs are
going to get faster, better and deeper at reading through and then
intentionally generating complexity
  3) As a human's cognition tires, the probability of reading errors rises
non-linearly which increases the probability of late mid-game and end game
errors - I think AlphaGo has already progressed pretty far in the end game

I'd consider these the three primary general vulnerabilities of human Go
playing against any future AI. Given AlphaGo's training mechanism is
actually search space exploration engine, it will slowly but surely explore
and converge on more optimal play in all three of these domains
significantly faster and cheaper than directly investing in and expending
human cognition efforts; i.e. professionals studying to do the knowledge
expansion and verification. And I think they will continue to optimize
AlphaGo's algorithms in both human and self-play.

The window where humans are going to be able to fish out a win against
AlphaGo is rapidly closing...and it may have already closed.


Other thoughts...

I think we are going to see some fascinating "discoveries" of errors in
existing very old josekis. At some point, I think we will even see one or
two new ones discovered by AIs or by humans exploiting AIs. We are going to
see some new center oriented fighting based on vastly more complex move
sequences which will result in an substantial increase in resignations at
the professional level against each other.

Said a slightly different way...even if Lee Sedol figures how how to get a
lead in a game during the opening, AlphaGo will just continue to elevate
the board complexity with each move until it is just beyond its opponent's
reading ability while staying well within it's own reading ability
constraints. IOW, complexity is now an AIs advantage. AlphaGo doesn't have
the human frailty of being nervous of a possible future mistake and then
altering its priorities by pushing winning by a higher margin as a buffer
against said future reading complexity mistake. IOW, AlphaGo is regulated
by it's algorithm's prioritizing the probability of win higher than the
amount of margin by which it could buffer for a win. What seems like a
weakness is turning out to be one hell of a strength.

Add to the fact that this kind of behavior by AlphaGo is denying it's
opponent critical information about the state of the game which is more
readily available in human-vs-human games; i.e. AlphaGo's will continue to
converge towards calmer and calmer play in the face of chaotic play. And
the calmer it becomes, the less "weakness surface area" it will have for a
human to exploit in attempting a win.

This is utterly fascinating to get to witness. I sure wish Don Daily was
still here to get to enjoy this.


On Thu, Mar 10, 2016 at 2:52 PM, Thomas Wolf  wrote:

> With at most 2x361 or so different end scores but 10^{XXX} possible
> different
> games, there are at least in the opening many moves with the same optimal
> outcome. The difference between these moves is not the guaranteed score
> (they
> are all optimal) but the difficulty to play optimal after that move. And
> the
> human and computer strengths are rather different.
>
>
> On Thu, 10 Mar 2016, uurtamo . wrote:
>
>
>> If that's the case, then they should be able to give opinions on best
>> first moves, best first two move combos, and best first three move combos.
>> That'd
>> be interesting to see. (Top 10 or so of each).
>>
>> s.
>>
>> On Mar 10, 2016 12:37 PM, "Sorin Gherman"  wrote:
>>
>>   From reading their article, AlphaGo makes no difference at all
>> between start, middle and endgame.
>>   Just like any other position, the empty (or almost empty, or almost
>> full) board is just another game position in which it chooses (one of)
>>   the most promising moves in order to maximize her chance of winning.
>>
>>   On Mar 10, 2016 12:31 PM, "uurtamo ."  wrote:
>>
>> Quick question - how, mechanically, is the opening being
>> handled by alpha go and other recent very strong programs? Giant
>> hand-entered or game-learned joseki books?
>>
>> Thanks,
>>
>> steve
>>
>>

Re: [Computer-go] Finding Alphago's Weaknesses

[Jim O'Flaherty]

I was surprised the Lee Sedol didn't take the game a bit further to probe
AlphaGo and see how it responded to [...complex kos, complex ko fights,
complex sekis, complex semeais, ..., multiple connection problems, complex
life and death problems] as ammunition for his next game. I think he was so
astonished at being put into a losing position, he wasn't mentally prepared
to put himself in a student's role again, especially to an AI...which had
clearly played much weaker games just 6 months ago. I'm hopeful Lee Sedol's
team has been some meta-strategy sessions where, if he finds himself in a
losing position in game two, he turns it into exploring a set of
experiments to tease out some of the weaknesses to be better exploited in
the remaining games.

On Thu, Mar 10, 2016 at 8:16 AM, Robert Jasiek  wrote:

> On 10.03.2016 00:45, Hideki Kato wrote:
>
>> such as solving complex semeai's and double-ko's, aren't solved yet.
>>
>
> To find out Alphago's weaknesses, there can be, in particular,
>
> - this match
> - careful analysis of its games
> - Alphago playing on artificial problem positions incl. complex kos,
> complex ko fights, complex sekis, complex semeais, complex endgames,
> multiple connection problems, complex life and death problems (such as Igo
> Hatsu Yoron 120) etc., and then theoretical analysis of such play
> - semantic verification of the program code and interface
> - theoretical study of the used theory and the generated dynamic data
> (structures)
>
> --
> robert jasiek
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Re: [Computer-go] AlphaGo won first game!

[Jim O'Flaherty]

Congratulations, AlphaGo and team. And by resignation! That's fantastic!

Anyone know where the tipping point was? Did Sedol get the end game order
just slightly off and AlphaGo took advantage? Or was their an earlier poor
move by Sedol and/or surprising (and good) move by AlphaGo? I'm WAY too
weak a player to even make stupid guesses. Any links to in depth analysis
would be greatly appreciated!

On Wed, Mar 9, 2016 at 1:46 AM, René van de Veerdonk <
rene.vandeveerd...@gmail.com> wrote:

> wow .. congrats to the AlphaGo team!!
>
> On Tue, Mar 8, 2016 at 11:43 PM, Hiroshi Yamashita 
> wrote:
>
>> AlphaGo won 1st game against Lee Sedol!
>>
>> Hiroshi Yamashita
>>
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Re: [Computer-go] Congratulations to Zen!

[Jim O'Flaherty]

Aja,

My anticipation couldn't be any higher, I don't think! I wish you and your
AlphaGo team the best of luck!


Namaste,

Jim

On Mon, Feb 22, 2016 at 10:12 AM, Aja Huang  wrote:

> Hi Ingo,
>
> On Mon, Feb 22, 2016 at 3:49 PM, "Ingo Althöfer" <3-hirn-ver...@gmx.de>
> wrote:
>>
>> By the way: is progress fine with respect to your March event?
>>
>
> We are still preparing hard for the match.
>
> Apologies I didn't answer many questions regarding AlphaGo and
> particularly value network, but I will have time to carefully read and
> answer those questions after the Lee Sedol match.
>
> AlphaGo is getting stronger and stronger. I hope you all will enjoy
> watching the games.
>
> Cheers,
> Aja
>
>
>>
>> Cheers, Ingo.
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Re: [Computer-go] Knowledge Details

[Jim O'Flaherty]

Robert,

How have these things emerged in the chess AI world following Deep Blue and
Kasperov's loss over a decade ago? To what degree does "human expert
details of chess theory matters" (where the term "matters" is pretty
squishy). From what I can see, that is not what happened and while I am not
privy to every detail of every motivation in the chess AI world, I'm
certainly not seeing this assertion or the supporting values arising to any
level of relevance, much less primacy.

And for those who were working in the Chess knowledge world, how was their
work, business, grants and funding affected by the Deep Blue/Kasperov
results and then the rapid improvement of more than one chess engine to
beyond the highest skilled humans? What happened to prize tournaments? To
what degree is it reasonable to predict a similar pattern will occur in and
about Go and those who are working in the Go knowledge world?

BTW, I have my own personal aspirations which have been thwarted by this
development. I have several thousand hours of doing my own research and
development (of my personal spare time outside my day job, over many years)
which has been rendered considerably less valuable (other than my own
personal development in the non-Go related parts). And I'm finding it
difficult to embrace this "change" as I had no idea just how much
motivation it created in the present having the Go AI goal as an inspiring
future. The loss of that motivation has created anxiety and uncertainty.

And even in spite of the loss and the grief I am experiencing in that loss,
I am still very enthusiastic about Aja and his team's achievements. And I
will be following all the teams who continue to work in this area. For
myself, I will now look for other ways to apply my knowledge, although I
will likely drift further away from Go as the focal point of motivation.

Best of luck finding your way through your meaning and value (emotional)
reintegration of this newest reality update.


Namaste,

Jim


On Wed, Feb 3, 2016 at 3:51 AM, Robert Jasiek  wrote:

> The current fashion favours general AI approaches forgoing knowledge
> details. Given enough calculation power applied to well chosen AI
> techiques, many knowledge details are redundant because they are generated
> automatically: AlphaGo does play (at least some) ko fights with ko threats,
> tesujis, test moves, (at least some) life and death or semeai problems etc.
> At the same time, AI calculation power is still not large enough to
> generate all human knowledge details. Aji with long-term impact and
> maintaining the life status "independently alive" instead of unnecessarily
> transforming it to "(ko|independently alive)" (aka "unsettled") are prime
> examples. Programs also play for the win regardless of whether moves are
> suboptimal for the score difference - human players tend to avoid such
> (programs would also profit from avoiding such to prevent losing when
> making a later mistake due to a knowledge gap related to insufficient error
> handling). There is another great threat related to knowledge details,
> which is not immediately apparent and will be even much less apparent when
> programs will exceed top human playing strength: A program can run into a
> situation where an infrequent knowledge detail becomes relevant. And a
> program can run into ordinary software or hardware bugs, something that
> must be detected and correct on the AI level.
>
> My conclusion is: human expert knowledge on details of go theory matters.
>
> There have been 9p players committing self-atari when filling a dame, so
> you might argue that programs may infrequently make similar blunders. When
> I issued a million dollar prize, I'd prefer human expert knowledge
> implemented at least as an additional layer of error handling.
>
> (Other fun includes internet connection trouble, server bugs of
> distributed computers, hardware bugs of the local interface computers or
> interrupted power supply.)
>
> --
> robert jasiek
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Re: [Computer-go] Mastering the Game of Go with Deep Neural Networks and Tree Search

[Jim O'Flaherty]

And to meta this awesome short story...

AI Software Engineers: Robert, please stop asking our AI for explanations.
We don't want to distract it with limited human understanding. And we don't
want the Herculean task of coding up that extremely frail and error prone
bridge.
On Feb 1, 2016 3:03 PM, "Rainer Rosenthal" <r.rosent...@web.de> wrote:

> ~~
> Robert: "Hey, AI, you should provide explanations!"
> AI: "Why?"
> ~~
>
> Cheers,
> Rainer
>
>> Date: Mon, 1 Feb 2016 08:15:12 -0600
>> From: "Jim O'Flaherty" <jim.oflaherty...@gmail.com>
>> To: computer-go@computer-go.org
>> Subject: Re: [Computer-go] Mastering the Game of Go with Deep Neural
>> Networks and Tree Search
>> Message-ID:
>> <
>> cakx5gkjc7j0uq_pmxyumyfre7r+7ydltigbna5oo7kvnzq7...@mail.gmail.com>
>> Content-Type: text/plain; charset="utf-8"
>>
>> Robert,
>>
>> I'm not seeing the ROI in attempting to map human idiosyncratic linguistic
>> systems to/into a Go engine.
>>
>
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Re: [Computer-go] Mastering the Game of Go with Deep Neural Networks and Tree Search

[Jim O'Flaherty]

Robert,

I'm not seeing the ROI in attempting to map human idiosyncratic linguistic
systems to/into a Go engine. Which language would be the one to use;
English, Chinese, Japanese, etc? As abstraction goes deeper, the nuance of
each human language diverges from the others (due to the way the human
brain is just a fractal based analogy making engine). The scare resource is
human mind power producing advances on the main goal making a superior AI
to what already exists. As the linguistic pathway hasn't emerged in Chess
in the last decade, then I find it considerably less likely it will end up
emerging for Go...unless you are, of course, suggesting that is something
you are taking up. :)

The AI world is changing to make explaining computation cognition to humans
less necessary, or even desirable. Why bound the solution space to only
what cognitively linguistically limited humans can imagine and/or consider?
And given even one AI team is thinking this way, the nature of competition
will drive other competing teams to similar motivation(s). Welcome to
"memetic evolution in action". Kind of makes those of us in the nearby
human cognitive domains just a wee bit more nervous about what is rapidly
approaching as human cognition automateable. For example, books about
josekis could be rendered far less valuable if/when AlphaGo and some other
AI competitor more strongly influenced by josekis pushes AlphaGo into new
spaces which involve much longer resolution horizons than humans used for
those that exist now.

No matter what, the future sure does sound very exciting now that Alpha Go
has broken the Go AI ceiling. I cannot WAIT to see the results of the event
against Lee Sedol.

Congratulations, Alpha Go team and Aja!


Jim


On Mon, Feb 1, 2016 at 12:50 AM, Robert Jasiek  wrote:

> On 01.02.2016 07:30, Petri Pitkanen wrote:
>
>> Explaining why the move is good in human terms is useless goal. Good chess
>> programs cannot do it nor it is meaningful. As the humans and computers
>> have vastly different approach to selecting a move then  by the definition
>> have reasons for moves. As an example your second item 'long-term aji',
>> For
>> human an important short cut but computer a mere result for seeing far
>> enough in the future or combining several features of postion into
>> non-linear/linear computation.
>>
>
> Such is not "useless" but requires additional research or implementation.
>
>
> --
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Re: [Computer-go] The Game AI Forum is back

[Jim O'Flaherty]

Tysvm for the clarification. I appreciate and agree with your reasons. :)

On Mon, Feb 1, 2016 at 8:20 AM, Rémi Coulom <remi.cou...@free.fr> wrote:

> I did not create a go sub-forum in order to not compete with this mailing
> list. As long as there is not a strong agreement of all the members of the
> list to move there, I feel that splitting into two online discussion places
> would be detrimental. I won't censor topics about the game of Go on
> game-ai-forum.org, though, if you really want to post there.
>
> Rémi
>
> On 02/01/2016 02:56 PM, Jim O'Flaherty wrote:
>
>> Richard,
>>
>> I'm probably missing the obvious, I went to the forum, but was unable to
>> find a forum specifically for Go. I found Abolone, Hex and several others.
>>
>>
>> Thank you,
>>
>> Jim
>>
>>
>> On Fri, Jan 1, 2016 at 9:08 AM, Richard Lorentz <richard.lore...@csun.edu
>> <mailto:richard.lore...@csun.edu>> wrote:
>>
>> Thank you very much. Personally I find it much easier to keep up
>> with and follow topics in this kind of format. Perhaps we can
>> encourage people who post on the mailing list to post on your
>> Forum instead/too?
>>
>> -Richard
>>
>> P.S. Happy New Year!
>>
>>
>> On 01/01/2016 12:56 AM, Rémi Coulom wrote:
>>
>> Hi,
>>
>> I had created the Game Programming Forum a few years ago. I
>> decided to put it online again, at a new URL:
>>
>> https://urldefense.proofpoint.com/v2/url?u=http-3A__www.game-2Dai-2Dforum.org_=CwIGaQ=Oo8bPJf7k7r_cPTz1JF7vEiFxvFRfQtp-j14fFwh71U=i0hg-cKH69CA5MsdosvezQ=k7ciuFNHc56S8sYi-wsSC3UjQqtMtd8vZwuQLSElt0U=Qe20Mv7Kkbe7tMuviF1S9NBlJEB_lWpPF2m-yVhiEJY=
>>
>> Maybe some of you will be interested to participate there.
>>
>> Rémi
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Re: [Computer-go] The Game AI Forum is back

[Jim O'Flaherty]

Richard,

I'm probably missing the obvious, I went to the forum, but was unable to
find a forum specifically for Go. I found Abolone, Hex and several others.


Thank you,

Jim


On Fri, Jan 1, 2016 at 9:08 AM, Richard Lorentz 
wrote:

> Thank you very much. Personally I find it much easier to keep up with and
> follow topics in this kind of format. Perhaps we can encourage people who
> post on the mailing list to post on your Forum instead/too?
>
> -Richard
>
> P.S. Happy New Year!
>
>
> On 01/01/2016 12:56 AM, Rémi Coulom wrote:
>
>> Hi,
>>
>> I had created the Game Programming Forum a few years ago. I decided to
>> put it online again, at a new URL:
>> https://urldefense.proofpoint.com/v2/url?u=http-3A__www.game-2Dai-2Dforum.org_=CwIGaQ=Oo8bPJf7k7r_cPTz1JF7vEiFxvFRfQtp-j14fFwh71U=i0hg-cKH69CA5MsdosvezQ=k7ciuFNHc56S8sYi-wsSC3UjQqtMtd8vZwuQLSElt0U=Qe20Mv7Kkbe7tMuviF1S9NBlJEB_lWpPF2m-yVhiEJY=
>> Maybe some of you will be interested to participate there.
>>
>> Rémi
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>>
>> https://urldefense.proofpoint.com/v2/url?u=http-3A__computer-2Dgo.org_mailman_listinfo_computer-2Dgo=CwIGaQ=Oo8bPJf7k7r_cPTz1JF7vEiFxvFRfQtp-j14fFwh71U=i0hg-cKH69CA5MsdosvezQ=k7ciuFNHc56S8sYi-wsSC3UjQqtMtd8vZwuQLSElt0U=jQCf3nlMALQtqhF8wjhxM1h1pfAZeKNbABS6uOdgKbU=
>>
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>
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Re: [Computer-go] Replicating AlphaGo results

[Jim O'Flaherty]

I think the first goal was and is to find a pathway that clearly works to
reach into the upper echelons of human strength, even if the first version
used a huge amount of resources. Once found, then the approach can be
explored for efficiencies from both directions, top down (take this away
and see what we lose, if anything) and bottom up (efficiently reoriginate a
reflection of a larger pattern in a much more constrained environment).
>From what I can see in the chess community, this is essentially what
happened following Deep Blue's win against Kasperov. And now their are
solutions on single desktops that can best what Deep Blue did with far more
computational resources.


On Thu, Jan 28, 2016 at 10:07 AM, Petr Baudis  wrote:

>   Hi!
>
>   Since I didn't say that yet, congratulations to DeepMind!
>
>   (I guess I'm a bit disappointed that no really new ML models had to be
> invented for this though, I was wondering e.g. about capsule networks or
> training simple iterative evaluation subroutines (for semeai etc.) by
> NTM-based approaches.  Just like everyone else, color me very awed by
> such an astonishing result with just what was presented.)
>
> On Wed, Jan 27, 2016 at 11:15:59PM -0800, David Fotland wrote:
> > Google’s breakthrough is just as impactful as the invention of MCTS.
> Congratulations to the team.  It’s a huge leap for computer go, but more
> importantly it shows that DNN can be applied to many other difficult
> problems.
> >
> > I just added an answer.  I don’t think anyone will try to exactly
> replicate it, but a year from now there should be several strong programs
> using very similar techniques, with similar strength.
> >
> > An interesting question is, who has integrated or is integrating a DNN
> into their go program?  I’m working on it.  I know there are several others.
> >
> > David
> >
> > From: Computer-go [mailto:computer-go-boun...@computer-go.org] On
> Behalf Of Jason Li
> > Sent: Wednesday, January 27, 2016 3:14 PM
> > To: computer-go@computer-go.org
> > Subject: Re: [Computer-go] Mastering the Game of Go with Deep Neural
> Networks and Tree Search
> >
> > Congratulations to Aja!
> >
> > A question to the community. Is anyone going to replicate the
> experimental results?
> >
> >
> https://www.quora.com/Is-anyone-replicating-the-experimental-results-of-the-human-level-Go-player-published-by-Google-Deepmind-in-Nature-in-January-2016
> ?
>
>   A perfect question, I think - what can we do to replicate this,
> without Google's computational power?
>
>   I probably couldn't have resisted giving it a try myself (especially
> given that a lot of what I do nowadays are deep NNs, though on NLP),
> but thankfully I have two deadlines coming... ;-)
>
>   I'd propose these as the major technical points to consider when
> bringing a Go program (or a new one) to an Alpha-Go analog:
>
>   * Asynchronous integration of DNN evaluation with fast MCTS.  I'm
> curious about this, as I thought this would be a much bigger problem
> that it apparently is, based on old results with batch parallelization.
> I guess virtual loss makes a lot of difference?  Is 1 lost playout
> enough?
> I wonder if Detlef has already solved this sufficiently well in
> oakfoam?
>
> What's the typical lag of getting the GPU evaluation (in, I guess,
> #playouts) in oakfoam and is the throughput sufficient to score all
> expanded leaf nodes (what's the #visits?)?  Sorry if this has been
> answered before.
>
>   * Are RL Policy Networks essential?  AIUI by quick reading, they are
> actually used only for RL of the value networks, and based on Fig. 4
> the value network didn't use policy network for training on but still
> got quite stronger than zen/crazystone?  Aside of extra work, this'd
> save us 50 GPU-days.
>
> (My intuition is that RL policy networks are the part that allows
> embedding knowledge about common tsumego/semeai situations in the
> value networks, because they probably have enough capacity to learn
> them.  Does that make sense?)
>
>   * Seems like the push for SL Policy Network prediction accuracy from
> 50% to 60% is really important for real-world strength (Fig. 2).
> I think right now the top open source solution has prediction
> accuracy 50%?  IDK if there's any other factor (features, dataset
> size, training procedure) involved in this than "Updates were
> applied asynchronously on 50 GPUs using DistBelief 60; gradients older
> than 100 steps were discarded. Training took around 3 weeks for 340
> million training steps."
>
>   * Value Networks require (i) 30 million self-play games (!); (ii) 50
> GPU-weeks to train the weights.  This seems rather troublesome, even
> 1/10 of that is a bit problematic for individual programmers.  It'd
> be interesting to see how much of that are diminishing returns and
> if a much smaller network on smaller data (+ some compromises like
> 

Re: [Computer-go] Number of 3x3 patterns

[Jim O'Flaherty]

Ah. That makes sense. It's a pattern centered on a possible next move. Very
cool. Tysvm for explaining.

On Tue, Nov 3, 2015 at 1:33 PM, Detlef Schmicker <d...@physik.de> wrote:

> -BEGIN PGP SIGNED MESSAGE-
> Hash: SHA1
>
>
>
> Am 03.11.2015 um 20:24 schrieb Jim O'Flaherty:
> > I don't see how "leave the center empty" works as a valid case,
> > assuming this it just any valid 3x3 window on the board. Given bots
> > playing each other, there can be 9x9 clumps of a stone of the same
> > color. I can see it being argued there is no computational value in
> > this specific pattern instance. But, then what are the conditions
> > of the exceptions to the generalization? And how do you effectively
> > iterate through the other +20,000 variations (not reduced by
> > location or color symmetry)?
> >
> > So, I'm curious, is there some other assumption about the 3x3
> > window other than it be a view into any valid 3x3 space on a Go
> > board?
>
> Sorry, I did not explain the details, the assumption is:
> I play in the middle, so it must be empty. I thought legal moves might
> not really reduce the number of 3x3 patterns, as there can be no
> suicide known from 3x3 patterns, as a capture is always possible.
>
> Therefore I wonder, what 14 patterns did not appear in my 4 games
> harvested:)
>
>
> >
> > On Tue, Nov 3, 2015 at 1:04 PM, Álvaro Begué
> > <alvaro.be...@gmail.com> wrote:
> >
> >> I get 1107 (954 in the middle + 135 on the edge + 18 on a
> >> corner).
> >>
> >> Álvaro.
> >>
> >>
> >>
> >> On Tue, Nov 3, 2015 at 2:00 PM, Detlef Schmicker <d...@physik.de>
> >> wrote:
> >>
> > Thanks, but I need them reduced by reflection and rotation
> > symmetries (and leave the center empty so 3^8 + 3^5 + 3^3 and than
> > reduce)
> >
> >
> >
> > Am 03.11.2015 um 19:32 schrieb Gonçalo Mendes Ferreira:
> >>>>> If you are considering only black stone, white, empty and
> >>>>> border, ignoring symmetry, wouldn't it be
> >>>>>
> >>>>> 3^9 + 3^6 + 3^4
> >>>>>
> >>>>> 3^9 for patterns away from the border, 3^6 for near the
> >>>>> sides and 3^4 near the corners, assuming you are also
> >>>>> interested in the center value.
> >>>>>
> >>>>> This makes 20493, then you need to take out illegal
> >>>>> patterns (surrounded middle stone). So I'd hint it's close
> >>>>> to 2.
> >>>>>
> >>>>> On 03/11/2015 18:17, Detlef Schmicker wrote: I could not
> >>>>> find the number of 3x3 patterns in Go, if used all
> >>>>> symmetrie s.
> >>>>>
> >>>>> Can anybody give me a hint, were to find. Harvesting 4
> >>>>> games I get 1093:)
> >>>>>
> >>>>> Thanks, Detlef
> >>>>>> ___
> >>>>>> Computer-go mailing list Computer-go@computer-go.org
> >>>>>> http://computer-go.org/mailman/listinfo/computer-go
> >>>>>
> >>>>> ___ Computer-go
> >>>>> mailing list Computer-go@computer-go.org
> >>>>> http://computer-go.org/mailman/listinfo/computer-go
> >>>>>
> >>> ___ Computer-go
> >>> mailing list Computer-go@computer-go.org
> >>> http://computer-go.org/mailman/listinfo/computer-go
> >>>
> >>
> >>
> >> ___ Computer-go
> >> mailing list Computer-go@computer-go.org
> >> http://computer-go.org/mailman/listinfo/computer-go
> >>
> >
> >
> >
> > ___ Computer-go mailing
> > list Computer-go@computer-go.org
> > http://computer-go.org/mailman/listinfo/computer-go
> >
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Re: [Computer-go] Number of 3x3 patterns

[Jim O'Flaherty]

I don't see how "leave the center empty" works as a valid case, assuming
this it just any valid 3x3 window on the board. Given bots playing each
other, there can be 9x9 clumps of a stone of the same color. I can see it
being argued there is no computational value in this specific pattern
instance. But, then what are the conditions of the exceptions to the
generalization? And how do you effectively iterate through the other
+20,000 variations (not reduced by location or color symmetry)?

So, I'm curious, is there some other assumption about the 3x3 window other
than it be a view into any valid 3x3 space on a Go board?

On Tue, Nov 3, 2015 at 1:04 PM, Álvaro Begué  wrote:

> I get 1107 (954 in the middle + 135 on the edge + 18 on a corner).
>
> Álvaro.
>
>
>
> On Tue, Nov 3, 2015 at 2:00 PM, Detlef Schmicker  wrote:
>
>> -BEGIN PGP SIGNED MESSAGE-
>> Hash: SHA1
>>
>> Thanks, but I need them reduced by reflection and rotation symmetries
>> (and leave the center empty so 3^8 + 3^5 + 3^3 and than reduce)
>>
>>
>>
>> Am 03.11.2015 um 19:32 schrieb Gonçalo Mendes Ferreira:
>> > If you are considering only black stone, white, empty and border,
>> > ignoring symmetry, wouldn't it be
>> >
>> > 3^9 + 3^6 + 3^4
>> >
>> > 3^9 for patterns away from the border, 3^6 for near the sides and
>> > 3^4 near the corners, assuming you are also interested in the
>> > center value.
>> >
>> > This makes 20493, then you need to take out illegal patterns
>> > (surrounded middle stone). So I'd hint it's close to 2.
>> >
>> > On 03/11/2015 18:17, Detlef Schmicker wrote: I could not find the
>> > number of 3x3 patterns in Go, if used all symmetrie s.
>> >
>> > Can anybody give me a hint, were to find. Harvesting 4 games I
>> > get 1093:)
>> >
>> > Thanks, Detlef
>> >> ___ Computer-go
>> >> mailing list Computer-go@computer-go.org
>> >> http://computer-go.org/mailman/listinfo/computer-go
>> >
>> > ___ Computer-go mailing
>> > list Computer-go@computer-go.org
>> > http://computer-go.org/mailman/listinfo/computer-go
>> >
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>> =j9hC
>> -END PGP SIGNATURE-
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>
>
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Re: [Computer-go] KGS bot tournaments - what are your opinions?

[Jim O'Flaherty]

I second Peter's response.
On Oct 10, 2015 10:33 AM, "Peter Drake"  wrote:

> I'm also for no limits, if only because there's no way to enforce them.
>
> If there is to be a limited division, I'd like to see all programs run on
> identical hardware.
>
> On Fri, Oct 9, 2015 at 6:07 AM, Hiroshi Yamashita 
> wrote:
>
>> Hi Nick,
>>
>> I'd like no limit. Restriction will lose a chance of massive
>> computer's programming. But one thread limit tournament
>> once a year may be interesting.
>>
>> I like (2), and (3) is nice, but I'm already happy with your reports!
>>
>> Regards,
>> Hiroshi Yamashita
>>
>>
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>
>
>
> --
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> https://sites.google.com/a/lclark.edu/drake/
>
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Re: [Computer-go] Goggernaut Russia+China vs The World stalled machine cycles

[Jim O'Flaherty]

I think you enjoy seeing what you write and/or visually concoct. And I'm
not sure anyone but you understands what you write and visually concoct. I
have the vague notion your shooting blindly into this cognitive space
hoping to hit a eureka mother lode; kind of like playing the lottery. Each
email or YouTube visual soup is your purchased lottery ticket into this
space hoping for a respect as the lottery win.

Finally, I'm not seeing how this particular post is related or connected to
computer Go. But, I'm also somewhat hesitant to ask you to explain the
connection, as I'm not willing to agree to read or watch what you might
produce as a response.
On Oct 3, 2015 5:02 PM, "djhbrown ."  wrote:

> .
> As a lifelong pacifist [2], i would prefer it had a kinder, gentler name,
> one that semiotically signifies United peoples, in contrast to the
> doublethink [3] NWO which really means OWN because everything doublethink
> means the opposite of what it says; as in 1913 when they said "Federal
> Reserve" which means "Private Bloodsucker" and in 1950 when they said
> "Foreign Relations" which means "Local Kiru" [5,6] and in 2001 when they
> said "They done it" which means "We done it" and again in 2008 when they
> said "Quantitative Easing" which means "Quantitative Tightening", because
> the effect of writing off the private debt of plutocrats who own the banks
> that own the Federal Reserve that issues the currency, is to dilute the
> purchasing power of the currency over which they have the stranglehold,
> thereby transferring the Wealth Of Nations from the masses to the
> plutocratic inner circle (ie, they WON [7]), thereby tightening the belts
> and reins and shackles of the robota [1] and again in 2014 when they said
> "IS" which means "ISNT".
>
> As it would be knowledgeable, it would be Gnostic.
>
> To reflect its Internationally Distributed Electronic Architecture, it
> should remind people of that true-to-life Land of Oz representative
> documentary called "Neighbours" in which everyone helps out each other like
> a supportive extended family (and Kylie is so cute she makes all the sweaty
> effort and expenditure of energy needed for meiosis worthwhile).
>
> Putting two and two together, that makes Gnostic United Neighbours, which
> can be abbreviated to its acronym, notwithstanding its proximity to an
> antediluvian bovine app, to save those precious stalled [8] machine cycles,
> so rare these days [4].
>
> References
> [1] http://en.wiktionary.org/wiki/robota#Czech
> [2]
> http://www.youtube.com/watch?v=cTaP5jQv2KI=1=PL4y5Wtsvtdurz6BhIIAnhF_0bbPr-edNd
> [3] http://www.orwelltoday.com/doublethink.shtml
> [4] http://www.theguardian.com/film/2007/feb/10/comedy.television
> [5] http://history.state.gov/historicaldocuments/frus1950v05/preface
> [6] http://glosbe.com/ja/en/kiru
> [7] http://www.ft.com/cms/s/0/10f42a56-6830-11e5-97d0-1456a776a4f5.html
> [8] http://stallman.org/stallman-computing.html
>
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Re: [Computer-go] Computer-go Digest, Vol 69, Issue 2

[Jim O'Flaherty]

You mean literally the slowest of all the constraints in all of software
engineering (excluding waiting on UI input) in a domain that cannot
currently get enough unconstrained CPU and memory cycles?

On Fri, Oct 2, 2015 at 8:53 AM, djhbrown .  wrote:

> .
> "sharing code is typically not going to be practical."
>
> that's not what i suggested.  perhaps someone else can explain the concept
> of message-passing distributed architecture better than me
>
>
>
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Re: [Computer-go] impact of AI on Go ... Where / How do i start ?

[Jim O'Flaherty]

Gonçalo wrote, "Well, I'd argue there is nothing inherently superior about
copying the human natural processes..."

I couldn't agree more! What inspires me about biological evolution is it's
fantastic use of temporal accretion compression; i.e. DNA viewed as
fractals. Given that meta-"natural process", I'm very much interested in
exploring emerging a Go playing mechanism from something similar; i.e.
creating simple leaf mechanisms which are then encoded into meta leafs,
which are then incorporated into meta-meta-leafs. The idea would be a
computational social organism approach to the game, from start to finish.

And if biological evolution is any intuitive informer in predicting the
outcome of this line of thinking, if what emerges is eventually capable of
playing high level Go, it will not be reducable to either human linguistic
nor human rational principals. Just because we thought up the rules in
human term doesn't require a computational player to cogitate in the same
way as the rules originator.
On Sep 27, 2015 6:41 AM, "Gonçalo Mendes Ferreira"  wrote:

> Well, I'd argue there is nothing inherently superior about copying the
> human natural processes, instead of using our intellect to find a way to
> achieve better results in simpler ways. Humans were also not born with
> domain over tools, or fire, do you suppose there are two kinds of people,
> the curious and the ones that didn't go extinct?
>
> Of course knowing about ourselves is interesting by itself, but I think we
> have already a good idea of how our brains work (at least while playing
> Go), and for practical reasons those same processes are just not as
> feasible to apply with the tools we have.
>
> If you are writing a Go program that attempts to be competitive, then it
> will be judged based on that. It doesn't make sense to complain that people
> are not writing competitive programs using techniques that showed poor
> returns in the past.
>
> Gonçalo F.
>
> As a sidenote, I'd be very much interested in a Go program that attempted
> to evaluate Go aesthetics, like Chesthetica did for western chess.
>
> On 09/27/2015 10:11 AM, djhbrown . wrote:
>
>> it rather depends on what you think AI is all about and what you want to
>> achieve.
>>
>> there are two kinds of people in the world: those who are curious, and
>> those who just want to make yet another cloned ticky-tacky mousetrap so
>> they can compete on the Go playing-field because they're no good at
>> football or kung-fu or [rest left unsaid].
>>
>> If you want to write a go-playing program in a hurry, don't waste your
>> time
>> talking to me; just do what most others do and just follow/copy Mogo/Crazy
>> Stone, possibly adding a tweak or two of your own, and stick your "look
>> ma,
>> no hands" robot on a server with all the others.
>>
>> If instead you would like to participate in a project to build a Go
>> program
>> that uses hierarchical planning and reasoning, you can talk to me.  You
>> could start by googling me and reading my papers and the papers of others
>> that reference mine.  And the ones that don't.  Start with De Groot's
>> seminal book entitled "Thought and Choice in Chess".  Then read everything
>> Herbert Simon has ever written.  And Minsky, and and and.
>>
>> Please be aware that i envisage it would take dozens of programmers dozens
>> of years for what i have in mind to get anywhere.  At 66, i won't live
>> long
>> enough to see it happen.  And even after all that effort, although a
>> program can be written that would be able to tell you what it is thinking
>> in a way that makes sense to people, it probably wouldn't perform at
>> shodan
>> level, let alone be as strong as Zen19, let alone a future "Son of Big
>> Blue
>> + Watson", which would probably use simple pattern-matching database
>> search
>> + MCTS blind random search and/or CNN or, more likely, a novel
>> variant/synthesis of them on a massively parallel computer.  Zen19's
>> authors tell me it improved its performance an entire rank by shifting
>> from
>> a single processor to 4 processors on a 1Gb Ethernet.  Watson has about
>> 30,000 processors on a 100Gb Ethernet i think.
>>
>> Whichever route you try, you are unlikely to get anywhere non-trivial
>> doing
>> it on your own, unless you are a Mozart of the keyboard and had produced
>> impressive programs by the age of 8 years old.  After you reach the ripe
>> old age of 19, your brain basically stops growing except for a few neurons
>> in your neocortex to stop you doing thoughtless teenage things; apart from
>> that, your learning curve is downhill from then on...
>>
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Re: [Computer-go] re comments on Life and Death

[Jim O'Flaherty]

I'm very much looking forward to your sharing your progress with us.
Perhaps you could give some more concrete examples of what you have done
already; i.e. where you have moved from the messy human
linguistic/cognitive "principles" to something much more formal?

On Thu, Sep 10, 2015 at 2:23 AM, Robert Jasiek  wrote:

> On 10.09.2015 08:24, David Fotland wrote:
>
>> I would say rather, that expert systems are dead in Go because many smart
>> and talented people, including professional experts, worked diligently for
>> two decades on this approach and none were able to get stronger than about
>> 5 kyu.  This is a strong experimental result, not an opinion.
>>
>
> This says nothing about the potential of expert systems when done right.
> General talent, professional expert system designers or professional
> players are insufficient. What is needed is a very good understanding of go
> theory on all topics of go theory as expert system knowledge.
>
>
> --
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Re: [Computer-go] re comments on Life and Death

[Jim O'Flaherty]

Awesome! Tysvm for replying and posting the link.

On Thu, Sep 10, 2015 at 4:26 AM, Robert Jasiek <jas...@snafu.de> wrote:

> On 10.09.2015 10:29, Jim O'Flaherty wrote:
>
>> Perhaps you could give some more concrete examples of what you have done
>> already; i.e. where you have moved from the messy human
>> linguistic/cognitive "principles" to something much more formal?
>>
>
> In my principles (or other theory), the degree of ambuigity varies from
> formal to ordinary language.
>
> Example of a formal formula:   dF =? 0
> where F is 'fighting liberties' and the formula applies to what I call
> 'class 1 semeais'.
>
> Example of (seemingly) ordinary language in a principle about defending
> life in a fight: "Maintain connection of a group's important strings."
> This is not ordinary language though but I use 'connection' and 'important
> string' as consistent terms in all my books, where the former is defined
> but the latter is (still) undefined.
>
> Consistent use of the same terms and defined concepts everywhere and well
> chosen definitions for the basic terms remove much of the mess and enable
> hierarchic design and use of principles etc.
>
> For several hundred further examples of definitions and principles, see my
> books and papers. For my first six of 11 books and earlier papers /
> messages, see the short overview
> http://home.snafu.de/jasiek/RobertJasiekGoTheoryResearch.html
>
>
> --
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>
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Re: [Computer-go] re comments on Life and Death

[Jim O'Flaherty]

I'm not convinced that it's reducible (as in reductionism) to get to a
rational (i.e. highly influenced by deterministic math) set of principles
to describe Go (which appears to be a precondition to getting it mapped
into your expert system). In fact, I don't think it can currently be done
for a static Go position (assuming one is attempting to projecting it into
the future to produce a probability about the outcome) unless it is in the
end game (where the complexity has be significantly pruned to leave a much
smaller search space). That said, I wish you the best of luck producing the
set of principles. I would LOVE to see that breakthrough as it implies so
many other awesome things.

I think we way underestimate how much complexity emerges from a single Go
position, much less projecting that complexity forward temporally. It's why
there is so much motivation to push MC as far as is possible. It tosses the
most of the complexity aside in favor of extremely high levels of brute
force combined with statistical analysis. And the engines that are
attempting to bridge MC with a relatively simplistic expert engine are now
finally approaching the upper levels of human cognitive ability (anything
above 5 dan amateur is well into the upper levels of human cognitive
ability in the domain of Go).

So, just in case there might be a breakthrough one or two more MC
iterations away, it's worth continuing to explore it even though it's
starting to feel like it's now stuck in a local optima in the Go engine
improvement search space. And I've personally been waiting for quantum
computing to give the MC strategy another good kick in the pants. And that
kick might be just enough to send it the rest of the way past the best
human's ability. If so, that will be tragic as it means that just like
Chess, brute force largely won...again.


On Wed, Sep 9, 2015 at 5:13 AM, Robert Jasiek  wrote:

> On 09.09.2015 09:53, Petri Pitkanen wrote:
>
>> Too many contradicting heurestics
>>
>
> The mid-term problem is not mutual contradiction of heuristics because
> their careful study can remove the contradictions and establish a hierarchy
> of principles. Only the problem of great number of principles to be coded
> and maybe of the complexity of time remain.
>
>
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Re: [Computer-go] re comments on Life and Death

[Jim O'Flaherty]

I disagree with the assertion MC must be the starting point. It appears to
have stagnated into a local optima; i.e. it's going to take something
different to dislodge MC, just like it took MC to dislodge the traditional
approaches preceding MC's introduction a decade ago. Ultimately, I think it
can serve to inform a higher level conceptual system

And while I don't get his videos (they are way to ADHD scattered and
discontinuous for my personal ability to focus and internalize), I think I
grok the general direction he'd like to see things head. And I am quite
ambivalent about the idea of creating and using linguistic semantic trees
as an approach, as much or even more than I was about MC when it emerged.

On Fri, Sep 4, 2015 at 10:55 AM, Stefan Kaitschick <
stefan.kaitsch...@hamburg.de> wrote:

> So far I have not criticised but asked questions. I am a great fan of the
> expert system approach because a) I have studied go knowledge a lot and
> see, in principle, light at the end of the tunnel, b) I think that "MC +
> expert system" or "only expert system" can be better than MC if the expert
> system is well designed, c) an expert system can, in principle, provide
> more meaningful insight for us human duffers than an MC because the expert
> system can express itself in terms of reasoning. (Disclaimer: There is a
> good chance that I will criticise anybody presenting his definitions for
> use in an expert system. But who does not dare to be criticised does not
> learn!)
>
> MC is currently stagnating, so looking at new (or old discarded)
> approaches has become more attractive again.
> But I don't think that a "classic" rules based system will be of much use
> from here. It is just too far removed from MC concepts to be productively
> integrated into an MC system. And no matter what, MC has to be the starting
> point, because it is so much more effective than anything else that has
> been tried.What you are left to work with, is the trail of statistics that
> MC leaves behind. That is the only tunnel with a possible end to it that I
> see. And who knows, maybe someone will find statistical properties that can
> be usefully mapped back to human concepts of go.
>
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Re: [Computer-go] Life and Death

[Jim O'Flaherty]

I think you forgot to suggest which pharmaceuticals, legal or otherwise, to
be using while watching this. Without said pharmacological assistance, that
video doesn't make a bit of sense to me.

On Wed, Sep 2, 2015 at 9:13 PM, djhbrown .  wrote:

>
> https://www.youtube.com/watch?v=opOAFYutILU=8=PL4y5WtsvtduqNW0AKlSsOdea3Hl1X_v-S
>
> --
> http://sites.google.com/site/djhbrown2/home
> https://www.youtube.com/user/djhbrown
>
>
>
>
>
>
>
>
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Re: [Computer-go] Congratulations to Zen!

[Jim O'Flaherty]

Nick,

I just had the same problem. Gmail is being over helpful by grouping all
emails with the exact same title as a thread. So, goto your Sent folder.
Look for the email with the Subject you just used. Notice there is a number
in parenthesis to the right indicating the number of emails in the
thread. Select that email. Scroll to the bottom. And if it is not already
 expanded, select the final email in the thread, and you should see the
one you sent.

I sure wish there was more options in Gmail around this behavior.

Jim O'Flaherty
 On Jan 12, 2015 7:59 AM, Nick Wedd mapr...@gmail.com wrote:

 Congratulations to Zen19S, undefeated winner of yesterday's 19x19 KGS
 bot tournament!

 My report is http://www.weddslist.com/kgs/past/109/index.html
 As usual, I hope you will report any errors or comments to me.

 Nick

 P.S. I am now using gmail as my mail client, and it refuses to show me
 any email which I wrote (like this one).  So I hope that at least one
 person
 will respond to this, and let me know that it has reached the mailing list.
 N

 --
 Nick Wedd  mapr...@gmail.com

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Re: [computer-go] is Zen gone commercial?

[Jim O'Flaherty, Jr.]

Darren,

If it doesn't work on Wine, you could always load a VM, like Sun's VirtualBox, 
install a copy of Windows in that and play from there. VirtualBox has very good 
performance metrics at above 95% of max (non VM) speed. And there's plenty of 
throw-away copies of XP licenses available all over the place as old systems 
retire and are replaced with newer hardware upon which Vista is now installed.


Jim






From: Darren Cook dar...@dcook.org
To: computer-go computer-go@computer-go.org
Sent: Thursday, September 24, 2009 8:00:03 AM
Subject: Re: [computer-go] is Zen gone commercial?

 It is already shipped in Japan, as Tencho no Igo.

http://soft.mycom.co.jp/pcigo/tencho/index.html

Looks like Windows only. Anyone know if it will run under wine on linux?
They are advertising it as 2-dan (i.e. Japanese 2-dan).

A rather pricey 13,400 yen, or 10,752 yen ($120) online.

Darren

-- 
Darren Cook, Software Researcher/Developer
http://dcook.org/gobet/  (Shodan Go Bet - who will win?)
http://dcook.org/mlsn/ (Multilingual open source semantic network)
http://dcook.org/work/ (About me and my work)
http://dcook.org/blogs.html (My blogs and articles)
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Re: [computer-go] Cross-Question on Pamplona

[Jim O'Flaherty]

Remi,

I find it interesting that he won with the slowest hardware. I am still 
wondering how much performance is still a low influencer. In other 
words, a really fast poor algorithm won't be a better algorithm on 
slower hardware (or slower software).



Jim


Rémi Coulom wrote:

Ingo Althöfer wrote:

Hello,
this is not Go, but I feel that some people here
should know the answer:

What are the results of the Connect6 competition
in the Computer Olympiad.

Thx in advance, Ingo.
  
I forwarded the question to organizers. I'll update the web site as 
soon as I have the results. Speed chess is also missing.


Also: congratulations to Yamato for the impressive victory of Zen, 
with the slowest hardware of the whole tournament.


Rémi
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Re: [computer-go] Cross-Question on Pamplona

[Jim O'Flaherty]

Oops...should have read ...a really fast poor algorithm won't be*_at_* 
a better algorithm on slower hardware...


Jim O'Flaherty wrote:

Remi,

I find it interesting that he won with the slowest hardware. I am 
still wondering how much performance is still a low influencer. In 
other words, a really fast poor algorithm won't be a better algorithm 
on slower hardware (or slower software).



Jim


Rémi Coulom wrote:

Ingo Althöfer wrote:

Hello,
this is not Go, but I feel that some people here
should know the answer:

What are the results of the Connect6 competition
in the Computer Olympiad.

Thx in advance, Ingo.
  
I forwarded the question to organizers. I'll update the web site as 
soon as I have the results. Speed chess is also missing.


Also: congratulations to Yamato for the impressive victory of Zen, 
with the slowest hardware of the whole tournament.


Rémi
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Re: [computer-go] Cross-Question on Pamplona

[Jim O'Flaherty]

Remi,

It's not so much a question, just a thought about the use of power.

Not every MC program is the same. And that's assuming you leave all the 
UCT/RAVE/etc. variations completely out of the comparisons. In fact, in 
my reading this list over the last 24 months, I would say it appears 
that the similarities between MC implementations are coarse grained. 
When you get down to the implementations, each MC program seems to be 
varying in the details. Some are light, others are heavy in their 
playouts. Some are including hand coded evaluators some of the time, 
others all the time thereby playing out fewer games per second. Some are 
playing deeper (auto stop on 9x9 at 200 moves, 300 moves, when b/w score 
ration exceeds a ratio threshold, etc.), some are playing broader 
(degree of distribution deepening particular nodes). If you were to try 
and map all of this into some genomic analogy, there would be lots of 
similarity in morphology (directly observable appearances), but huge 
differences at the genes. And the optimal effectiveness/performance 
ratio devil is in the details.


So, when two programs play each other and they both assert they are MC 
programs, I am not sure much is really be said in terms of the 
comparison, other than MC has become Go's equivalent of the marketing 
term multi-media in the PC world. It now includes so much, it's hard 
to call it a distinction any more.


That said, it means that one MC program might be using it's power much 
more effectively (require substantially less CPU cycles to produce a 
similarly skilled result) than another, even though both assert they are 
MC.


Perhaps it would be better said that a Go program has an MC 
characteristic rather than saying it is an MC program; association 
versus identity.



Jim


Rémi Coulom wrote:

Jim O'Flaherty wrote:

Remi,

I find it interesting that he won with the slowest hardware. I am 
still wondering how much performance is still a low influencer. In 
other words, a really fast poor algorithm won't be a better algorithm 
on slower hardware (or slower software).



Jim 
Hardware has a lot of influence on playing strength. I noticed an 
improvement of about 100 Elo points for a doubling of computing power 
(19x19). This is against other MC programs. Against humans, the 
improvement is less.


I am not sure if this was your question. A poor algorithm won't be a 
better algorithm on slower hardware, but I am not sure what it means.


Rémi
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Re: [computer-go] Git, any other ideas?

[Jim O'Flaherty, Jr.]

Mark,

I would figure that given the popularity of both Eclipse and git, the problems 
connecting the two easily, similar to the way Eclipse and Subversion connect, 
will be solved sooner rather than later. And once they are, it won't be too 
difficult to transition from whatever you choose to use in the interim. It's 
not like the core framework project is going to have a ton of supported 
branches or even contributors, right?

BTW, I don't recall why you were moving off of Subversion. Why not stay there 
for the interim unless you have lots of coders who will be working on the 
framework (as opposed to being a client using the framework .jar-s). I figure 
the JAGS framework would only have a couple of contributors. It's the clients 
of the framework who want to experiment with the least investment in install, 
set up and indefinitely tinker who will gain advantage. And they don't need 
version control at all. Almost all of them will just be consuming the framework 
.jar-s and likely doing the development alone. And for those who are part of a 
team (or are just have to work with a one), they will be choosing their own VCS 
completely decoupled from the choices around the development of the JAGS 
framework.


Jim






From: Mark Boon [EMAIL PROTECTED]
To: computer-go computer-go@computer-go.org
Sent: Friday, October 24, 2008 3:13:09 PM
Subject: Re: [computer-go] Git, any other ideas?


On 24-okt-08, at 16:15, Zach Wegner wrote:

 Use git anyways ;) I don't use an IDE, but git works great for me from
 the command line. After I realized that git in pkgsrc was actually
 GNU Interactive Tools and not git, it took me just a few minutes to
 set up. The basic commands are really easy to learn, especially if you
 are familiar with CVS/SVN. There are also separate GUI frontends for
 git, so that might be an option worth looking at.


Over my dead body :)

If I don't get similar integration in Eclipse as Subversion I'm not  
interested.

Now trying Mercurial. Also problems there, as it complains about some  
python library. At least the Eclipse plugin installed without a hitch.

Mark

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Re: [computer-go] yet a mogo vs human game

[Jim O'Flaherty, Jr.]

What were the software improvements? Were they related to the code distributing 
the work, or to the actual game playing/move selection code?


Jim




- Original Message 
From: Robert Waite [EMAIL PROTECTED]
To: computer-go@computer-go.org
Sent: Wednesday, August 27, 2008 9:54:14 AM
Subject: [computer-go] yet a mogo vs human game


* - MoGo was using 5% of Huygens (instead of 25% against Kim);
* - there were some software improvements
* - MoGo won 2 out of 3 games in 9x9 (even games)
* - MoGo won with handicap 5 in 19x19 against the 6D player


That is interesting... it used 1/5th of the processing power and
got approximately the same rank (about 1 Dan). From what I gather..
Kim believed it was 2 or 3 Dan? I guess this is because a 9 stone
handi starts to make the stone per rank estimation get a bit fuzzy.


It is mentioned that there was a software improvement. I wonder how
much the software improvement made up for the reduction in processing
power since it seems to have stayed approximately the same rank. Or could

it mean that dividing the computation strength by 5 did not change
the relative strength of Mogo by much?
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[computer-go] What was the specific design of the Mogo version which beat the pro...

[Jim O'Flaherty]

All,

Can anyone detail the design of the version of Mogo that beat the 
professional? Or is there a web-page where at least the general approach 
has been described? Is the information even public? I am not seeing the 
the implementation details, just the overall design and general 
strategies. However, if the implementation details are available, I 
would love to see those as well.


I am confused around what Mogo used. Was it Monte Carlo only, UCT only, 
Monte Carlo integrated with UCT, RAVE, etc? I have read through all of 
the recent emails, and I have not been able to get a clear picture of 
it's design. Mogo at one timed used Monte Carlo and UCT. I read an email 
that the one that played the pro and won did not use UCT at all. 
However, I thought the massive tests that Don did awhile back showed 
that MC did not scale very well, but MC + UCT did.


And what language/platform is Mogo written in; C/C++, Java, Assembly, 
PHP, etc.? And how did the language/platform choice impact the overall 
efforts; speed them up, slow them down, complicate/ease creating the 
parallelism on the super computer, etc.?


So, I am now confused precisely what method or methods were used and/or 
integrated to produce the current scalable version of Mogo. I want to 
know these details so I can at least get a better sense of what actually 
occurred with the win. I don't care near as much about the hardware as I 
do the software architecture and design.



Thank you,

Jim

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Re: [computer-go] Re: linux and windows

[Jim O'Flaherty, Jr.]

All,

Another option is to use a VM, MS's Virtual PC (free), VMWare's offering (free 
for non-commercial use) or any of the flavors of the open source Xen. 
Basically, you can set up an install of whatever target environment you use as 
a client OS. And then install and configure all you need and want natively 
within the Client OS without having to worry that the host OS is Windows.

And for those of you who will say this is inefficient - I would just reply 
with, not participating at all is less efficient than at least participating 
with something inside a VM. There is no need for perfection, as in having every 
little tiny bit of performance eeked out of a box/processor/memory. If you can 
get +90% (which is what all the above VM creators claim for each of theirs), 
then you can participate and gain more experience for your particular 
computer_go player.


Jim




- Original Message 
From: Don Dailey [EMAIL PROTECTED]
To: [EMAIL PROTECTED]; computer-go computer-go@computer-go.org
Sent: Thursday, July 17, 2008 1:31:21 PM
Subject: Re: [computer-go] Re: linux and windows



terry mcintyre wrote:
 A cygwin port can't really be considered a windows application since it 
 requires that the windows user install cygwin. This is not for the faint of 
 heart.

 There are many good reasons why some people develop on Linux. Porting between 
 Linux and Windows is not trivial. 

 A better way to run linux programs on borrowed Windows machines might be to 
 burn a LiveCD with one's program -- something akin to the Hikarunix CD, which 
 tournament organizers could then pop into a computer, boot, and start the 
 program.
  
But you can compile using mingw32 to build native applications.I 
recently compiled my chess program and it runs fine, at least on recent 
windows OS versions - of course it is a UCI program which means the GUI 
is a separate windows program.

- Don





  
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[computer-go] Mobile phone go player/client/recorder...

[Jim O'Flaherty, Jr.]

All,

What's available in terms of a quality Go game player/client/recorder for 
mobile phones? I have a Windows Mobile 6 phone (ATT Tilt - 8925) and would 
like to be able to play the occasional casual game, be able to connect and play 
with someone else on their mobile phone or desktop PC and to be able to use the 
client to record games in progress and store them as .sgf files.

I have already been to http://www.vieka.com/gnugo/ and that is a very nice 
start. However, it does not have the ability to play someone else except on the 
same phone. And it does not have a way to save a game or generate an .SGF.

Any URLs to existing products would be deeply appreciated.

BTW, it is not very useful that the game is named Go. I tried to Google for 
Windows Mobile Go Game and got lots of useless hits. The word Go is too 
common and only has a very weak relation to the Asian board game.


Thank you,

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Re: [computer-go] My experience with Linux

[Jim O'Flaherty, Jr.]

I'll second both the original poster (his troubles with Linux mirrored mine) 
and the reply (I was completely enthralled with Ubuntu...WOW!).

Jim

- Original Message 
From: Álvaro Begué [EMAIL PROTECTED]
To: computer-go computer-go@computer-go.org
Sent: Wednesday, April 9, 2008 10:18:11 AM
Subject: Re: [computer-go] My experience with Linux

Get ubuntu (http://www.ubuntu.com/). You can ask them to send you a
free CD. And you should consider getting a decent Internet connection.

Álvaro.


On Wed, Apr 9, 2008 at 10:54 AM,  [EMAIL PROTECTED] wrote:
  I got excited about the free software sometime ago and bought a copy of
 Susie Linux. But the installation always hang up at some point and can never
 complete. I had to kiss my $20 goodbye and so much for the Linux. Recently
 my job involves embedded Linux. For whatever reason we used the Fedora
 version 4. It looks like the Windows 3.1. The newest version may be more
 modernized, which I don't have tme to fnd out. The Linux operatng system is
 about 600 Mbyte compressed. Since we have a fast internet, it took only 40
 min. to download. After downloading we needed to find a software that can
 write ISO format on CDs. I failed to find such a software on the internet
 and ended up use the trial version of Nero. Then the Nero I installed
 highjacked my CD drive and I had to unnstall it later.  I also tried the
 64-bit version of Linux and the installation never worked.

  I begin to consder install Linux on my PC at home. With my internet
 connection speed, downloading 600 MB is just unrealistic. The other option
 is to order CD's. They cost $45 and up and I'm sure this cost will go up
 with time. So much for the free software. I keeps asking myself what will
 happen if the installation fails. I only have one computer and one internet
 connection.

  Not that I don't trust other people's opinion, but people pitched other
 things before which we never hear again.


  DL



 
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Re: [computer-go] speeding up testing of computer go programs

[Jim O'Flaherty, Jr.]

Heikki,

I'm with you.  There is no wrong thinking at the present time.  There 
are too many differing agendas, with building the strongest program 
immediately being only one, to claim any approach is futile, inefficient 
or erred.  Once there are approaches that actually come near playing low 
dan levels against humans, I can see how narrowing approaches and 
thinking will become useful.  Until then, lots of chaotic and random 
path experimentation is desirable, including other languages, 
specialized languages, techniques, etc.



Jim


Heikki Levanto wrote:

On Sun, Nov 25, 2007 at 11:52:14AM -0500, Don Dailey wrote:
  

I know that most go programmers don't concern themselves with small
improvements because of the sense that there is bigger fish to fry.   
But this is wrong thinking.   If you can get 10 small improvements it
can be equivalent to one very large improvement.  




This is frong thinking *for you*. Wasn't it yourself who said that people
program go for various reasons, only one of them being making the strongest
possible program. A person with a more theoretical approach might lament
that all that speed optimizing indeed improved the play considerably, but has
not produced any new insight or theory on how best to approach the problem. A
mere amateur like me could complain about the time invested in those small
improvements, that I did not gain any new knowlege for myself, it was just
routine programming.  I humbly suggest that none of us (including you :-) is
guilty of wrong thinking.

Regards

   Heikki

  
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Re: [computer-go] speeding up testing of computer go programs

[Jim O'Flaherty, Jr.]

Don,

I think we have a semantic problem.  Some things don't work as expected 
but provide the genesis for further creativity.  Other things work, but 
not with sufficient additional value for the disproportionate effort 
invested.  Some things don't end up having any enduring value except as 
one of the many infinite possible paths eliminated.


Maybe we are being too abstract here.  If you have the time and 
motivation, would you please tell me in a couple of sentences what your 
standard(s) is upon which you can clearly distinguish right thinking 
from wrong thinking?  And how that standard accommodates active random 
walk experimentation and creativity such that an experimenter can know 
PRIOR to doing the experiment if he is headed off in a right or wrong path?



Jim


Don Dailey wrote:

Jim O'Flaherty, Jr. wrote:
  

Heikki,

I'm with you.  There is no wrong thinking at the present time.  



Of course there is wrong thinking.  Why do you think they call it the
trial and error approach?

- Don




  

There are too many differing agendas, with building the strongest
program immediately being only one, to claim any approach is futile,
inefficient or erred.  Once there are approaches that actually come
near playing low dan levels against humans, I can see how narrowing
approaches and thinking will become useful.  Until then, lots of
chaotic and random path experimentation is desirable, including other
languages, specialized languages, techniques, etc.


Jim


Heikki Levanto wrote:


On Sun, Nov 25, 2007 at 11:52:14AM -0500, Don Dailey wrote:
  
  

I know that most go programmers don't concern themselves with small
improvements because of the sense that there is bigger fish to fry.   
But this is wrong thinking.   If you can get 10 small improvements it
can be equivalent to one very large improvement.  



This is frong thinking *for you*. Wasn't it yourself who said that people
program go for various reasons, only one of them being making the strongest
possible program. A person with a more theoretical approach might lament
that all that speed optimizing indeed improved the play considerably, but has
not produced any new insight or theory on how best to approach the problem. A
mere amateur like me could complain about the time invested in those small
improvements, that I did not gain any new knowlege for myself, it was just
routine programming.  I humbly suggest that none of us (including you :-) is
guilty of wrong thinking.

Regards

   Heikki

  
  



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Re: [computer-go] Re: The global search myth

[Jim O'Flaherty, Jr.]

Seo,

All I described was the scientific method plus simple probability theory 
combined with using intuition to explore unknown unknowns creatively.  
For a layman's explanation into this world, see the works by Talib of 
Fooled by Randomness and The Black Swan.


Not sure about your analogy either.  If their theory is Extra 
Terrestrial Intelligence exists, has their been evidence provided to 
invalidate the theory?  I had not heard of any.  And our existence 
certainly supports the speculation within the theory, i.e. We exist.  
Therefor it is possible other intelligence exists.  And I am suspicious 
any evidence invalidating the core theory (given it is a simple and 
encompassing as I have summarized above) could be found anyway.  It 
would require searching the entire universe in a very short period of 
time as longer periods of time, like millions of years allow for 
possible emergence of evolutionary life forms after the area has been 
searched.


As to your then applying the analogy to computer chess/go - don't see 
the connection.



Jim


Sanghyeon Seo wrote:

2007/11/23, Jim O'Flaherty, Jr. [EMAIL PROTECTED]:
  

Don,

I think it is tenuous to predict, much less emphatically assert, that
just because the evidence is linear at the lower scale, it remains so at
higher scales.  While it is reasonable to assume, it is not certain.  I
see your point that at this time, your theory about it applying to
larger scales has yet to be invalidated.  However, this does not
preclude your theory being invalidated in the future.  Nor does it make
their intuitions about ways others might be able to do so (and keep an
open mind about creating attempts) as superstitious.  It just means they
are yet to be convinced of your position just as you are yet to be
convinced of theirs.  Remember, the direct evidence used to support a
theory that the world was flat.  That theory was later invalidated and
replaced with a new theory incorporating the old evidence as well as the
new evidence.



This starts to sound like a SETI advocate. After forty years of
sustained failures, the burden of proof is on SETI advocates, not
critics. Same goes for computer chess and computer go.

  
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Re: [computer-go] Re: The global search myth

[Jim O'Flaherty, Jr.]

Don,

I think it is tenuous to predict, much less emphatically assert, that 
just because the evidence is linear at the lower scale, it remains so at 
higher scales.  While it is reasonable to assume, it is not certain.  I 
see your point that at this time, your theory about it applying to 
larger scales has yet to be invalidated.  However, this does not 
preclude your theory being invalidated in the future.  Nor does it make 
their intuitions about ways others might be able to do so (and keep an 
open mind about creating attempts) as superstitious.  It just means they 
are yet to be convinced of your position just as you are yet to be 
convinced of theirs.  Remember, the direct evidence used to support a 
theory that the world was flat.  That theory was later invalidated and 
replaced with a new theory incorporating the old evidence as well as the 
new evidence.


And you want other attempting to disprove your theory.  It both educates 
them on the current theory and challenges and possibly convinces them to 
share holding your theory.  And it also educates you in the event they 
find some error in your approach/assumptions/context/definitions or are 
actually able to disprove your conclusion.  And it is likely someone 
will eventually disprove your theory while keeping the evidence upon 
which your theory rests.


I would encourage you to keep your theory (every cycle's sacred, every 
cycle's great, if cycle's wasted, God gets quite irate) and work making 
assumptions based upon this being true.  That's efficient.  I would also 
encourage others to challenge your theory and work at invalidating your 
assumptions around low level efficiencies.  Both you, they and 
computer_go will be stronger because of it.



Jim


Don Dailey wrote:

Hi Dave,

You are doing it.No matter what evidence is presented,  people will
find a way to say it doesn't exist.As I mentioned earlier, the
argument was that didn't apply to chess except for the first 4 or 5 ply
- then when that didn't happen they expanded it to the first 6 or 7 and
to this very day people are denying it - although they are looking more
and more foolish in the process.

We have already seen that this holds in GO, I did a massive study of it
month ago on 9x9 boards and showed everyone this beautiful plot with
straight lines showing the ELO per TIME curve which was essentially flat.  


I also remember the response.   ok,  it applies to a small boards but
19x19 is a completely different game that bears no resemblance. 


So I must give up on this.   I know if I do the plot again someone will
say,   it only applies to depths we can currently test.   Surely it
will flatten out next year when the new processors come.

I cannot answer to those arguments when no evidence is presented to back
it up other than superstition of disbelief or my favorite, the
testimony of experts in the field.  I can only say that every bit
of evidence we have backs up what I am saying.   


- Don


Dave Dyer wrote:
  

I agree with your exposition of search as it applies to chess, but
I think there is a qualitative difference in Go.

In chess, evaluators can see clear progress, in the form of material 
balance and statically determined positional factors, so each additional 
ply gives you more opportunity to see progress.


Until Go evaluators give similarly strong and reliable signals, search
will be a very much weaker tool.

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Re: [computer-go] Language

[Jim O'Flaherty, Jr.]

Colin,

I would NOT recommend this site.  It was last updated in '98.  Many of 
the optimizations listed were great for back then.  They are terrible 
for 2007 and will likely result in SLOWER execution, not faster.


For example, the claim is that a synchronized method call is 10 times 
slower than one which is not synchronized.  While true in '98, this has 
changed considerably and is now patently false.  The cost of 
acquiring/releasing a lock in most modern production available VMs is 
now measured in parts of a percent.  It is rarely worth optimizing this 
out as the constraint(s)/bottleneck(s) are very likely elsewhere.  
Completely changing your architecture to attempt to avoid 
synchronization is now bad for your code (if you have any intentions to 
make it multi-thread capable).


Another claim is marking a method final in an attempt to promote it to 
be inlined by the compiler.  In '98, this could have a substantial 
impact on performance.  Now, it not only does not desirably impact 
performance, the modern JVMs have sophisticated implementations around 
inlining including inlining based on probability with exceptions 
branched out of a default execution flow path (making the exceptions 
slower, but the default path the fastest), it makes the class(es) less 
flexibly to future adaptation.


If you are writing high performance Java code, it is worth your while to 
find references that are no more than 4 years old.  The JVMs have change 
so much in the last 10 years, any assumptions from a recent as 4 years 
ago are likely fallacious.


If you want to follow performance trends and very fixated execution 
performance engineering for Java, I would recommend starting here:

http://www.javaperformancetuning.com/

And for a book:
http://www.amazon.com/exec/obidos/ASIN/0596003773/javaperforman-20

I have used both the site and the book for my own Java performance 
tuning.  Excellent stuff.



Jim


Colin Kern wrote:

On Nov 20, 2007 1:56 PM, Nick Apperson [EMAIL PROTECTED] wrote:

  

On Nov 20, 2007 12:48 PM, Stefan Nobis [EMAIL PROTECTED] wrote:




Colin Kern [EMAIL PROTECTED] writes:

  

I think the reason for Ruby being so much slower is because it is an
interpreted language rather than a compiled language.


It's not the main problem (interpreted languages are slower than those
compiled to native code, but than even Java and C# are interpreted and
don't have such big slowdowns).
  

Java and C# are both compiled at some point if the same loop is running
repeatedly.  Java is usually compiled just in time which is to say as each
function is first run.  I'm not sure how C# is executed, but I think it gets
compiled before execution.




I just found this looking around for things about Java's speed.  Looks
like some useful ways to boost Java's performance.
http://www.cs.cmu.edu/~jch/java/speed.html

-Colin
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Re: [computer-go] Language

[Jim O'Flaherty, Jr.]

Nick,

When I engage in complex multi-threaded distributed processing, I have found 
Java to give me the most value for my limited personal time buck. I am not 
claiming that Java is competitive in performance with hand crafted assembly (or 
C or C++).  I am claiming that I have experienced a many fold increase in my 
productivity by exploiting the much easier to use the language, libraries, the 
distributed computing ability and JVMs of Java than attempting to reliably 
reproduce the same results in hand crafted assembly (or C, or C++, or 
equivalents in terms of raw machine performance).  For me, the primary 
constraint I am attempting to optimize is my own personal productivity.  I am 
willing to give up small percentages of computation performance in trade for 
being vastly more productive in generating experiments.  And at this point, JVM 
efficiencies have become so effective, we are talking about small percentages 
of performance difference.  They are close enough
 for me to easily choose away from the less portable, flexible and shareable 
implementations of libraries I have seen for pretty much any other 
implementation system (Java is more than a language, it is also libraries, JVM 
implementations, standards for inter-system communication, distributed 
computing, etc.).

I still contend that breakthroughs in programming Go are going to come from 
creative experimental algorithms as opposed to a couple percent optimization 
around current algorithms.  As such, I will remain wanting to favor 
implementation flexibility over computational efficiency.  Once we have 
breakthroughs worth optimizing (and from what I am reading here, there aren't 
any yet), I will carefully reconsider my choice of Java.  Recall there was a 
member of this forum who reported as his team went from Java to C/C++ to make 
things more efficient for his own implementation.  He described the resulting 
loss of coding efficiency was not worth the minimal gain in execution 
performance.  That member has since moved his team back to Java acknowledging 
there are efficiency benefits in C/C++, but that Java keeps them able to 
experiment with alternative approaches more rapidly.

As to Java taking over the world - that is kind of too late.  It's everywhere.  
Last calculation is that it is running on over 3 billion machines and devices 
(PCs, mainframes, mobile phones, smart cards, etc.).  And now that it is GPLed, 
it will find many more homes.  And I find it difficult to believe that the core 
reason there are so many machines and devices running Java to be the fact that 
Java has garbage collection.  I will grant you that it is likely an influencer, 
but not near the magnitude you seem to believe it is.  Java garbage collection 
is just one of many benefits collaborating with other language and library 
features which also influence the choice to implement in Java.

I sense you think that a gain for Java is a loss for C/C++.  I don't see it 
that way.  The market continues to expand adding more and more software 
engineers/developers/programmers.  So while C/C++ may not have the same growth 
rates it had in the '90s, there is still growth.  Why does it matter to you 
that Java is growing?  If you are happy with what you have chosen, why is what 
other people are recommending and choosing important to you?  What are you 
defending?  What are you trying to achieve?


Jim


- Original Message 
From: Nick Apperson [EMAIL PROTECTED]
To: computer-go computer-go@computer-go.org
Sent: Tuesday, November 13, 2007 12:07:10 AM
Subject: Re: [computer-go] Language

WARNING: This digresses into a rant by the end...  You've been warned.

If you like to have your garbage collected for you then use one of the 
management strategies present in C++.  If you like delayed freeing, overload 
new or use a library that does this.  Really, the difference between C++ and 
most other programming languages (that are strongly typed) is that C++ doesn't 
make any assumptions about what you are going to do with it because of its most 
basic principle: you don't pay for what you don't use.  If you want garbage 
collection, you can have it: it's not like C++ prevents this.  By the same 
token, Java and C# don't allow you to make any decision here which might be 
best in certain circumstances, but it certianly isn't always ideal.  If you 
want the subset of features that say java has, you are welcome to create these 
restrictions in C++ all while remaining more portable.


I personally use garbage collection every once in a while in my C++ code.  It 
is not usually the right tool for me, but there are circumstances where it 
makes sense.  I generally use it when I have data that isn't really owned by 
any object.  It is data that many parts of the program reference and some wish 
to keep a copy for themselves.  This is how the std::string class is 
implemented in C++.  Reference counting and copy on write.


But I'll be damned if Java takes over the 

Re: [computer-go] Intelligence

[Jim O'Flaherty, Jr.]

All,

For reasons similar to those mentioned by others, I have found the 
phrase artificial intelligence to be less than adequate to convey my 
interests in this domain.  And after considerable time, I came up with a 
term that I prefer; synthetic awareness.  It comes from having 
interests in several different domains which feed into my interest in 
fabricating non-homo-sapien memetic propagation.


First, synthetic is more inclusive.  It means that borrowing and 
incorporating specialized awareness/knowledge from organic/memetic 
domains is included and acceptable.  It also means that fabrication of 
new awareness/knowledge from strictly computation domains also works.


Secondly, awareness is more expansive than knowledge.  Boolean 
mathematic frames (proof focused rule based systems) and the symbolic 
efficiencies around linguistics (must be able to be articulated 
accurately) have most intellectuals fixated on producing idealized 
knowledge.  And while there is significant value in the results 
produced, the results (to me) are too sequential and fragile to be 
expected to scale up to extremely high levels of complexity.  This is 
why computer Checkers/Draughts is solved, computer Chess is not solved 
but beat the highest skilled humans, and computer Go is not even 
effectively beating low ranking amateurs.  Awareness covers much more 
complex notions like the subtleties implied in intuition and creativity.


Here is my reframing of a statement by a psychology author, Nathanial 
Branden:

STATEMENT_REFRAME
The need to create synthetic awareness has acquired a new urgency in 
the computational age.  The more rapid then rate of change, the more 
fragile and dangerous it is to operate computers mechanically, relying 
on routines of Boolean software and Boolean behavior that may be 
irrelevant or obsolete.

/STATEMENT_REFRAME

As has been discussed ad infinitum here on computer_go, I don't see 
computer Go be solved meaning like Checkers/Draughts has been solved.  
I do think it is achievable to generate some sort of computational 
result which can eventually outplay the humans of the highest skill.  I 
also think some significant breakthroughs are required around the move 
away from booleans (perfect move-vs-imperfect move) and towards scalars 
(probability of each available move will lead to overall increased value).


While the domain of the rules of Go feel very rigid, the complexity is 
so vast that any idealized solution is going to turn out to be a local 
optima, i.e. with enough effort and exploration, it will be discovered 
the idealized solution, too, has weaknesses which can be exploited and 
eventually cause it's failure.  As such, the more dynamic and creative 
the nature of the resulting entity, the more likely it will be the 
entity can eventually hop out of the local optima in search of an even 
higher optima.  The more reserved, risk averse and rigid the entity, 
the more likely it will be unable to move forward and the sooner it will 
succumb to another entity's discovering it's weaknesses and eventually 
out-playing it.


Go is the perfect game for demonstrating that even with a perfectly 
rigid foundation, the solution space is vastly more effectively searched 
via dynamic evolving mechanisms than via static rigid mechanisms.  And 
as can be seen with the recent UCT/MC results, we are still just barely 
above randomness in terms of discovering and inventing solutions.



Jim


Erik van der Werf wrote:

On 7/21/07, Weimin Xiao [EMAIL PROTECTED] wrote:

Intelligence is the ability to adapt or learn.


A hypothetical almighty oracle that already knows the correct answer
to every question and the right response in every situation would
never have to adapt. Hence evidence of intelligence according to your
definition would not be observed.

IMO the adaptation is just a means to an end. The end (Intelligence,
whatever it is) does not necessarily require adaptation.

Erik
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Re: [computer-go] Intelligence

[Jim O'Flaherty, Jr.]

Erik,

In perfect theory, I agree with you.  In the practicality of attempting 
to generate more effective computer Go players, I disagree.


In theory, there is a perfect girlfriend for me.  In practicality, there 
is my adapting to make the current girlfriend good enough and better, 
with perfection never really obtainable.



Jim


Erik van der Werf wrote:

On 7/21/07, Weimin Xiao [EMAIL PROTECTED] wrote:

Intelligence is the ability to adapt or learn.


A hypothetical almighty oracle that already knows the correct answer
to every question and the right response in every situation would
never have to adapt. Hence evidence of intelligence according to your
definition would not be observed.

IMO the adaptation is just a means to an end. The end (Intelligence,
whatever it is) does not necessarily require adaptation.

Erik
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Re: [computer-go] Intelligence

[Jim O'Flaherty, Jr.]

How do you know this is incorrect?  Are you claiming omniscience?

[EMAIL PROTECTED] wrote:
No. Erik is wrong even in theory. An arguement can fault in two 
aspects:assumption and logic. His arguement faults on the former, even 
his logic is iron clad. He assumed the existence of an Oracle, which 
we all know is incorrect.
  


-Original Message-
From: Jim O'Flaherty, Jr. [EMAIL PROTECTED]
To: computer-go computer-go@computer-go.org
Sent: Sun, 22 Jul 2007 10:40 am
Subject: Re: [computer-go] Intelligence

Erik, 
 
In perfect theory, I agree with you. In the practicality of attempting 
to generate more effective computer Go players, I disagree. 
 
In theory, there is a perfect girlfriend for me. In practicality, 
there is my adapting to make the current girlfriend good enough and 
better, with perfection never really obtainable. 
 
Jim 
 
Erik van der Werf wrote: 
 On 7/21/07, Weimin Xiao [EMAIL PROTECTED] 
mailto:[EMAIL PROTECTED] wrote: 
 Intelligence is the ability to adapt or learn. 
 
 A hypothetical almighty oracle that already knows the correct answer 
 to every question and the right response in every situation would 
 never have to adapt. Hence evidence of intelligence according to your 
 definition would not be observed. 
 
 IMO the adaptation is just a means to an end. The end (Intelligence, 
 whatever it is) does not necessarily require adaptation. 
 
 Erik 
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Re: [computer-go] 9x9 games wanted and the next big challenge

[Jim O'Flaherty, Jr.]

Chrilly,

The purpose of investment is to generate a return exceeding the original 
investment, i.e. a profit.  Given the state of Go, I am finding it 
difficult to imagine why an investor would choose to put any good money 
into Go.  There is absolutely no reliable expectation that Go will 
achieve even close to strong amateur status (1D) in the next couple of 
years.  It's possible some wealthy person might decide to generously 
donate money into the computer Go domain so as to forward his own 
passion, just as many of the people here generously donate their own 
very valuable personal time.  Go is not a reasonable place to put 
investments.  At present and from everything I can see, computer Go 
development depends upon personal passion and generosity.  And sans a 
huge breakthrough, I am currently unable to see this changing anytime soon.


That said, I think once Go AI becomes sufficiently and robustly skilled 
to reliably start giving strong amateurs (1D) genuinely competitive 
games, you will start to see investment rise.  And given a sufficiently 
high enough rate of change (objectively measured as increases in playing 
skill), you will start to see the investments accelerate as competition 
will spur on more innovation resulting in more successes resulting in 
more investment resulting in further innovation...and a positive 
feedback loop will be boot strapped.  As the probability of producing 
profits rise, the risk around insufficient returns on an investment 
fall.  Eventually a threshold is crossed and the system becomes 
self-generative.


Succinctly put - there is no money in computer Go (at least compared to 
computer Chess) because there is currently no hope (mathematically 
speaking) of the existing crop of computer Go programs to scale up to 
anything less than moderate amateur levels.  Once this changes from no 
hope to a remote possibility, the investment around Go will likely follow.


No to be too Zen here, but...the sooner you accept things as they are 
and stop resisting what is, the sooner you become free to move 
forward.  Go investment is working exactly as it ought, in relation to 
the whole.


Finally, thank you for your contribution to computer Go.  I get that it 
is an act of generosity (realistically, what else could it possibly 
be).  And I personally appreciate it.



Jim


chrilly wrote:



Sil wrote:

How about http://home.wwgo.jp/jp/minigo/


It seems that only 24 games are available. Is the whole collection
available somewhere?
Rémi

I have read dozens of times that computer-Go is the next big challenge.
But in fact it is a completly amateuristic field where even the most 
basic things are missing. As a chess programmer I did not even think 
about, that it is a problem to get a good game collection. There are 
no proper interfaces, no serious tournaments, a wired data standard...
AND there is no money involved:  For professional programming I get 
60Euro/h (1Euro=1.35$).

2.000h x 60 = 120.000 Euro.
This equation is of course completly wrong. One can not make in 2000h 
a very strong Go programm and one can not earn 120.000 Euro with it.

A more realistic equation is;
20.000 Euro/5000h = 4Euro/h.

The minimum wage (by law) is in Austria 6Euro/h. Obviously Go 
programming is even more unqualified than washing dishes in a restaurant.


If it would be really a big challenge, there would be some money. In 
chess nowadays there is also no money. But once it was a good business 
and there was some considerable money for Deep Blue and on a smaller 
scale also for Hydra, there was Don's project at MIT, one got a big 
Cray for Cray-Blitz, Ken Thompson build a chess engine
Its like some hobbyst engineers and hobby-pilots would try to fly to 
the moon.
Its probably only good for to write some academic papers. In this case 
its even an advantage that everything is so amateuristic. The general 
level is low and one can be the one-eyed king under blind ones.


Its clear to me that things are as they are in the West. Go is played 
only by a small freak community. But if it is so important in 
China/Korea/Japan why is'nt there something like Fritz and ChessBase? 
Or does it exist and we are living in a completly other Go-world?


Chrilly

P.S.: I do not want to offend anyone in this list. Everybody here does 
his best. I am just feed up with the things as they are.




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Re: [computer-go] 9x9 games wanted and the next big challenge

[Jim O'Flaherty, Jr.]

David,

Very well said.  Thank you.


Jim


David Doshay wrote:

Chrilly,

It is hard to disagree with what Jim writes, but I will in a small way.

When I recently flew to Asia, the screen on the seatback in front of 
me offered Go as one of its games. At its highest level it played far 
worse than the average program on CGOS or in a KGS computer 
tournament, and yet somebody was paid by that airline for the use of 
that program. And Go++ makes a living for its programmer.


There is money to be made in computer Go, but as Jim states, right now 
the risk/reward ratio does not encourage most normal investors, so it 
is for either 1) those with a high risk threshold, 2) those who think 
more about research than production, 3) those motivated by how hard it 
is and not put off by how much effort it is going to take, or 4) 
programmers of other games who underestimate how hard it really is. 
Please do not take offense by number 4. I have huge respect for your 
programming ability and am glad that you have joined us.



Cheers,
David



On 8, Jul 2007, at 8:36 AM, Jim O'Flaherty, Jr. wrote:


Chrilly,

The purpose of investment is to generate a return exceeding the 
original investment, i.e. a profit.  Given the state of Go, I am 
finding it difficult to imagine why an investor would choose to put 
any good money into Go.  There is absolutely no reliable expectation 
that Go will achieve even close to strong amateur status (1D) in the 
next couple of years.  It's possible some wealthy person might decide 
to generously donate money into the computer Go domain so as to 
forward his own passion, just as many of the people here generously 
donate their own very valuable personal time.  Go is not a reasonable 
place to put investments.  At present and from everything I can see, 
computer Go development depends upon personal passion and 
generosity.  And sans a huge breakthrough, I am currently unable to 
see this changing anytime soon.


That said, I think once Go AI becomes sufficiently and robustly 
skilled to reliably start giving strong amateurs (1D) genuinely 
competitive games, you will start to see investment rise.  And given 
a sufficiently high enough rate of change (objectively measured as 
increases in playing skill), you will start to see the investments 
accelerate as competition will spur on more innovation resulting in 
more successes resulting in more investment resulting in further 
innovation...and a positive feedback loop will be boot strapped.  As 
the probability of producing profits rise, the risk around 
insufficient returns on an investment fall.  Eventually a threshold 
is crossed and the system becomes self-generative.


Succinctly put - there is no money in computer Go (at least compared 
to computer Chess) because there is currently no hope (mathematically 
speaking) of the existing crop of computer Go programs to scale up to 
anything less than moderate amateur levels.  Once this changes from 
no hope to a remote possibility, the investment around Go will likely 
follow.


No to be too Zen here, but...the sooner you accept things as they 
are and stop resisting what is, the sooner you become free to move 
forward.  Go investment is working exactly as it ought, in relation 
to the whole.


Finally, thank you for your contribution to computer Go.  I get that 
it is an act of generosity (realistically, what else could it 
possibly be).  And I personally appreciate it.



Jim


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Re: [computer-go] Re: pseudoliberties

[Jim O'Flaherty, Jr.]

What's a pseudo-liberty?  And how can there be more of them than there are 
empty intersections (81) on the board?

- Original Message 
From: Jason House [EMAIL PROTECTED]
To: computer-go computer-go@computer-go.org
Sent: Thursday, March 29, 2007 1:02:01 PM
Subject: Re: [computer-go] Re: pseudoliberties

After some trial and error, I got 90

 * * * * 
*
 * * * * 
* * * ***
* * *
*** * * *
 * * * * 
*
 * * * * 


On 3/29/07, John Tromp [EMAIL PROTECTED] wrote:
On 3/29/07, John Tromp [EMAIL PROTECTED] wrote:

 Is 88 the maximum number of pseuoliberties a string can have on 9x9?

Make that 89:-)

-John

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