Re: [Computer-go] Announcement in Leela

2018-04-27 Thread Sorin Gherman 
 Of course it defeated amateur 5d on DGS, LeelaZero has already
reached/surpassed top human pro strength, see recent news:

https://www.reddit.com/r/baduk/comments/8ezgms/leela_zero_20_blocks_4x_v100_tesla_gpu_just/
https://www.reddit.com/r/cbaduk/comments/8e7d21/andy_liu_1p_aga_vs_leela_zero_2_stones_handicap/



On Fri, Apr 27, 2018 at 5:09 PM mic  wrote:

> LeelaZero seems to have got a boost in strength. It just happened to
> beat a 5d player on DGS:
> https://www.dragongoserver.net/game.php?gid=1214911
>
> Beginning of this year it still lost against fuego bot by a big margin.
>
> Let's hope it's not just luck.
>
> -Michael.
>
> ---
> Diese E-Mail wurde von Avast Antivirus-Software auf Viren geprüft.
> https://www.avast.com/antivirus
>
> ___
> 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

Re: [Computer-go] Zero performance

2017-10-20 Thread Sorin Gherman 
Training of AlphaGo Zero has been done on thousands of TPUs, according to
this source:
https://www.reddit.com/r/baduk/comments/777ym4/alphago_zero_learning_from_scratch_deepmind/dokj1uz/?context=3

Maybe that should explain the difference in orders of magnitude that you
noticed?


On Fri, Oct 20, 2017 at 10:44 AM, Gian-Carlo Pascutto  wrote:

> I reconstructed the full AlphaGo Zero network in Caffe:
> https://sjeng.org/dl/zero.prototxt
>
> I did some performance measurements, with what should be
> state-of-the-art on consumer hardware:
>
> GTX 1080 Ti
> NVIDIA-Caffe + CUDA 9 + cuDNN 7
> batch size = 8
>
> Memory use is about ~2G. (It's much more for learning, the original
> minibatch size of 32 wouldn't fit on this card!)
>
> Running 2000 iterations takes 93 seconds.
>
> In the AlphaGo paper, they claim 0.4 seconds to do 1600 MCTS
> simulations, and they expand 1 node per visit (if I got it right) so
> that would be 1600 network evaluations as well, or 200 of my iterations.
>
> So it would take me ~9.3s to produce a self-play move, compared to 0.4s
> for them.
>
> I would like to extrapolate how long it will take to reproduce the
> research, but I think I'm missing how many GPUs are in each self-play
> worker (4 TPU or 64 GPU or ?), or perhaps the average length of the games.
>
> Let's say the latter is around 200 moves. They generated 29 million
> games for the final result, which means it's going to take me about 1700
> years to replicate this. I initially estimated 7 years based on the
> reported 64 GPU vs 1 GPU, but this seems far worse. Did I miss anything
> in the calculations above, or was it really a *pile* of those 64 GPU
> machines?
>
> Because the performance on playing seems reasonable (you would be able
> to actually run the MCTS on a consumer machine, and hence end up with a
> strong program), I would be interested in setting up a distributed
> effort for this. But realistically there will be maybe 10 people
> joining, 80 if we're very lucky (looking at Stockfish numbers). That
> means it'd still take 20 to 170 years.
>
> Someone please tell me I missed a factor of 100 or more somewhere. I'd
> love to be wrong here.
>
> --
> GCP
> ___
> 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

Re: [Computer-go] sgf files for world go championship games?

2017-03-24 Thread Sorin Gherman 
SGFs here:

http://lifein19x19.com/viewtopic.php?f=18=14117=World

On Fri, Mar 24, 2017 at 9:55 AM, Ray Tayek  wrote:

> any one got a pointer to these?
>
> thanks
>
>
> --
> Honesty is a very expensive gift. So, don't expect it from cheap people -
> Warren Buffett
> http://tayek.com/
>
> ___
> 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

Re: [Computer-go] Densei-sen

2016-03-23 Thread Sorin Gherman 
Why did darkforest resign? I think darkforest shoud be able to win by about
4 points if it keeps playing.


On Tue, Mar 22, 2016 at 11:55 PM, Hiroshi Yamashita 
wrote:

> Hi,
>
> darkforest lost against Koichi Kobayashi with 3 handicaps.
> Next game, Zen vs Kobayashi will be played also with 3 handicaps.
>
> Hiroshi Yamashita
>
> ___
> 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

Re: [Computer-go] Game 4: a rare insight

2016-03-13 Thread Sorin Gherman 
There is no way to not know that O10 was dead after white plays O9, since
AlphaGo handled much more complicated fights even in the games in October.

My only guess from looking at the sequence around O10, where black makes
its own big group bigger is that it was preparing for a ko-fight, and
wanted to have ONE huge ko-threat in that area, something like that - I
don't see any other reasonable explanation.

On Sun, Mar 13, 2016 at 7:55 AM, Olivier Teytaud 
wrote:

> Should we understand that AlphaGo had not understood that O10 was dead ?
> (sorry for Go beginner question :-) )
>
___
Computer-go mailing list
Computer-go@computer-go.org
http://computer-go.org/mailman/listinfo/computer-go

Re: [Computer-go] Congratulations to AlphaGo

2016-03-12 Thread Sorin Gherman 
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"  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 
>> 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
>>
>>
>> ___
>> 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

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

2016-03-10 Thread Sorin Gherman 
For that reason I guess that AlphaGo opening style is mostly influenced by
the net that is trained on strong human games, while as the game progresses
the MC rollouts have more and more influence in choosing a move.
Is my understanding way off?
On Mar 10, 2016 12:40 PM, "Thomas Wolf" <tw...@brocku.ca> wrote:

> But at the start of the game the statistical learning of infinitessimal
> advantages of one opening move compared to another opening move is less
> efficient than the learning done in the middle and end game.
>
> On Thu, 10 Mar 2016, 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 ." <uurt...@gmail.com> 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
>>
>>   On Mar 10, 2016 12:23 PM, "Thomas Wolf" <tw...@brocku.ca> wrote:
>> My 2 cent:
>>
>> Recent strong computer programs never loose by a few points.
>> They are either
>> crashed before the end game starts (because when being
>> clearly behind they play more
>> desperate and weaker moves because they mainly get negative
>> feadback from
>> their search with mostly loosing branches and risky play
>> gives them the only
>> winning sequences in their search) or they win by resignation
>> or win
>> by a few points.
>>
>> In other words, if a human player playing AlphaGo does not
>> have a large
>> advantage already in the middle game, then AlphaGo will win
>> whether it looks
>> like it or not (even to a 9p player like Michael Redmond was
>> surprised
>> last night about the sudden gain of a number of points by
>> AlphaGo in the
>> center in the end game: 4:42:10, 4:43:00, 4:43:28 in the
>> video https://gogameguru.com/alphago-2/)
>>
>> In the middle and end game the reduced number of possible
>> moves and the
>> precise and fast counting ability of computer programs are
>> superior.  In the
>> game commentary of the 1st game it was mentioned that Lee
>> Sedol considers the
>> opening not to be his strongest part of the game.  But with
>> AlphaGo playing
>> top pro level even in the opening, a large advantage after
>> the middle game
>> might simply be impossible to reach for a human.
>>
>> About finding weakness:
>> In the absense of games of AlphaGo to study it might be
>> interesting to get a general idea by checking out the games where 7d Zen
>> lost on KGS
>> recently.
>>
>> Thomas
>>
>> On Thu, 10 Mar 2016, wing wrote:
>>
>>   One question is whether Lee Sedol knows about these
>> weaknesses.
>>   Another question is whether he will exploit those
>> weaknesses.
>>   Lee has a very simple style of play that seems less
>> ko-oriented
>>   than other players, and this may play into the hands of
>> Alpha.
>>
>>   Michael Wing
>>
>>  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 whe

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

2016-03-10 Thread Sorin Gherman 
>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
> On Mar 10, 2016 12:23 PM, "Thomas Wolf"  wrote:
>
>> My 2 cent:
>>
>> Recent strong computer programs never loose by a few points.  They are
>> either
>> crashed before the end game starts (because when being clearly behind
>> they play more
>> desperate and weaker moves because they mainly get negative feadback from
>> their search with mostly loosing branches and risky play gives them the
>> only
>> winning sequences in their search) or they win by resignation or win
>> by a few points.
>>
>> In other words, if a human player playing AlphaGo does not have a large
>> advantage already in the middle game, then AlphaGo will win whether it
>> looks
>> like it or not (even to a 9p player like Michael Redmond was surprised
>> last night about the sudden gain of a number of points by AlphaGo in the
>> center in the end game: 4:42:10, 4:43:00, 4:43:28 in the video
>> https://gogameguru.com/alphago-2/)
>>
>> In the middle and end game the reduced number of possible moves and the
>> precise and fast counting ability of computer programs are superior.  In
>> the
>> game commentary of the 1st game it was mentioned that Lee Sedol considers
>> the
>> opening not to be his strongest part of the game.  But with AlphaGo
>> playing
>> top pro level even in the opening, a large advantage after the middle game
>> might simply be impossible to reach for a human.
>>
>> About finding weakness:
>> In the absense of games of AlphaGo to study it might be interesting to
>> get a general idea by checking out the games where 7d Zen lost on KGS
>> recently.
>>
>> Thomas
>>
>> On Thu, 10 Mar 2016, wing wrote:
>>
>> One question is whether Lee Sedol knows about these weaknesses.
>>> Another question is whether he will exploit those weaknesses.
>>> Lee has a very simple style of play that seems less ko-oriented
>>> than other players, and this may play into the hands of Alpha.
>>>
>>> Michael Wing
>>>
>>>  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
 >  ___
 >  Computer-go mailing list
 >  Computer-go@computer-go.org
 >  http://computer-go.org/mailman/listinfo/computer-go [1]



  Links:
  --
  [1] 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
>>

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

2016-03-10 Thread Sorin Gherman 
I doubt that the human-perceived weaknesses in AlphaGo are really
weaknesses - after the second game it seems more like AlphaGo has
"everything under control".
Professional players will still find moves to criticize, but I want to see
proof that any such move would change the fate of the game :-)

Sorin Gherman

On Thu, Mar 10, 2016 at 10:13 AM, wing <w...@swcp.com> wrote:

> One question is whether Lee Sedol knows about these weaknesses.
> Another question is whether he will exploit those weaknesses.
> Lee has a very simple style of play that seems less ko-oriented
> than other players, and this may play into the hands of Alpha.
>
> Michael Wing
>
> 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 <jas...@snafu.de> 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
>>> ___
>>> Computer-go mailing list
>>> Computer-go@computer-go.org
>>> http://computer-go.org/mailman/listinfo/computer-go [1]
>>>
>>
>>
>>
>> Links:
>> --
>> [1] 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] Territory counting library?

2007-12-25 Thread Sorin Gherman 
Is there any open-source library that does (estimated) territory counting?

Can GnuGo be easily modified to achieve territory counting?

The reason I need this is because I integrated GnuGo on my website:
http://www.361points.com/computergo/#gnugo and when both sides pass I
want to show not only the score estimation (GnuGo does that) but also
to show what each color's territories are.

I can imagine that when territories are closed and dead groups are
marked, a flood-fill algorithm will correctly find territories, but
I'm considering the case when territories aren't completely closed.

Thanks,
Sorin Gherman
___
computer-go mailing list
computer-go@computer-go.org
http://www.computer-go.org/mailman/listinfo/computer-go/