On 04.09.2015 07:25, David Fotland wrote:
group strength and connection information
For this to work, group strength and connection status must be a)
assessed meaningfully and b) applied meaningfully within a broader
conceptual framework. What were your definitions for group strength and
con
Could you please stop posting your videos to this list? I find nothing of
value in them. If others disagree, please speak up.
Álvaro.
On Thu, Sep 3, 2015 at 11:31 PM, djhbrown . wrote:
>
>
> https://www.youtube.com/watch?v=IoO7Nhlf_k4&list=PL4y5WtsvtduqNW0AKlSsOdea3Hl1X_v-S&index=10
>
> Pleas
> Many Faces of Go gives reasons for its moves after fact. It reasons about
> the position using go proverbs, life and death analysis, group strength and
> connection information, etc. If you have a copy, you can ask it to explain
> its reasons for making a move.
>
Many Faces of Go is a propriet
(Hello, I'm new to this mailing list)
Some of the things you say remind me of Mentifex style AI ramblings, but
again, I did enjoy what I watched of the videos, so it's at least
entertaining in a weird way even if it doesn't produce any breakthrough
in computer Go.
Try mixing some weird music
Robert, David Fotland has paid his dues on "truly intelligent" go programs.
Maybe more than anybody else.
I find your critique a little painful. Don't blame David, that the "stupid"
monte carlo works so much better.
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Computer-g
When I click on a youtube video, I don't expect much. But I do expect to be
at least marginally entertained.
One more video of this "quality", and you will have lost me as a potential
viewer.
On Fri, Sep 4, 2015 at 5:31 AM, djhbrown . wrote:
>
>
> https://www.youtube.com/watch?v=IoO7Nhlf_k4&list
I've been wrapping my head about dynamic komi adjustments for MCTS,
namely on the thesis by the Pachi creator, Petr Baudic.
On value-based situational compensation the author uses the average on
win rates from the previous simulations to decide whether or not to
change the komi. But I don't se
On 04.09.2015 15:55, Stefan Kaitschick wrote:
Robert, David Fotland has paid his dues on "truly intelligent" go programs.
Maybe more than anybody else.
I find your critique a little painful. Don't blame David, that the "stupid"
monte carlo works so much better.
So far I have not criticised but
> Robert, David Fotland has...
> I find your critique a little painful.
I don't think Robert was critiquing - he was asking for David's
definition of group strength and connection strength.
> the "stupid" monte carlo works so much better.
Does it? I thought "stupid" monte carlo (i.e. light play
Probably you've got this question multiple times, but I'd still like to ask.
Why not implement your ideas as a computer program? In my opinion
programming languages are much better in expressing logical, computational
ideas than natural languages. You can also "see" how well your ideas work.
2015.
On 04.09.2015 16:54, Minjae Kim wrote:
Why not implement your ideas as a computer program?
- I lack time.
- Developing my ideas has consumed decades.
- I know that there are gaps in my ideas that I need to research in when
I will have the additional time: some ideas are formulated for humans
The best contenders may be best for entirely different reasons. How do you
compare a line that tries to bring down a huge group with a line that
cautiously tries to optimize safe points. It's really hard to do. And
whereever the dynamic komi lands, pedestrian variations may look great or
totally un
On 04/09/2015 16:29, Stefan Kaitschick wrote:
The best contenders may be best for entirely different reasons. How do
you compare a line that tries to bring down a huge group with a line
that cautiously tries to optimize safe points. It's really hard to do.
That's for the search policy to deci
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
syste
On 04.09.2015 17:55, Stefan Kaitschick wrote:
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
No. It is also possible to construct it the other way round. Start with
an expert system. Whenever that
> "When I click on a youtube video, I don't expect much. But I do expect to
> be at least marginally entertained"
>
In ancient Rome, the plebeia (commoners) were ruled by a government
comprising an Emperor and a Senate. Plebs had no say in how society
functioned, but they were allowed to allowed
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
Learned rules from pure stats might be good guiding posts, but the pure
checking of millions of board positions is always going to be necessary.
My $0.02,
s.
On Sep 4, 2015 3:49 PM, "Jim O'Flaherty" wrote:
> I disagree with the assertion MC must be the starting point. It appears to
> have stagn
Convolution neural networks seem to be all the rave (no pun intended)
right now. To me they do seem more intuitive in recreating the process
of a human being recognizing patterns and getting a general feel of the
game, and then focusing on only a few sequences. Maybe they are limited
by the dat
I'd like to introduce a paper presented a few days ago in CIG2015,
Taiwan.
The main idea is to enlarge the KL-divergence between optimal move and
others by biasing the threshold of win/loss in MCTS algorithms. Not
exactly the same as dynamic komi but similar and I believe it has some
(stron
Many Faces of Go is MC + expert system (plus local search, etc). The reason I
won the world championship in 2008 is because I implemented MCTS but
incorporated the old Many Faces expert system move generator and ranking. This
is pretty slow (a few hundred positions a second), so when the tree
No. Since MF's search is so highly pruned, and directly by the expert system
move generator, it scales poorly with computer power. If I went back to the
pure MFGO engine and added the modern ELO based pattern from Remi's approach, I
think it would be a couple of stones stronger, but still weak
Probably everyone does something different for Dynamic komi. There have a few
publications.
In MFGO, the shipping version 12 doesn’t use dynamic komi, but the KGS version
has it, and it's probably worth about half a stone. My algorithm tries to keep
the win rate between 55% and 60% when win
Some details at http://www.smart-games.com/knowpap.txt
Completely agree that connections and group strength estimates are key to
strength, and are very difficult to get right. There are many tricky cases.
For connections I used shapes and local tactics to determine connectivity and
threat poi
I forgot, I did publish a paper on Many Faces:
https://www.researchgate.net/publication/220174515_Static_Eye_Analysis_in_The_Many_Faces_of_Go
I'm not sure it's available online.
David
> -Original Message-
> From: Computer-go [mailto:computer-go-boun...@computer-go.org] On
> Behalf Of Ro
thank you for sharing the paper.
"the Maximum Frequency method is based on the
maximization of the difference between the expected reward of
the optimal move and that of others"
intuitively it feels that biasing random search towards the optimal route
would yield reduced failure rates, yet it doe
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