Re: [Computer-go] New paper by DeepMind

I believe that the dependence of C(s) (formerly c_puct) on N(s) is new. The file pseudocode.py in the supplementary download sets c_base to 19652 and c_init to 1.25. Dan On Thu, Dec 6, 2018 at 5:27 PM Rémi Coulom wrote: > Hi, > > The new alphazero paper of DeepMind about chess and

Re: [Computer-go] Paper “Complexity of Go” by Robson

point if you are interested in the topic, as you seem to be: https://www.apaonline.org/page/nonsexist (the American Philosophical Association's "Guidelines for Non-Sexist Use Of Language"). Searching for "gender-fair language" on the internet will turn up

Re: [Computer-go] 9x9 is last frontier?

with MCTS; some have already used is an MCTS-ab algorithm that does exactly this. At the leaves, I call a qsearch() for evaluation whereas AlphaZero uses Value Network (no playouts ). Daniel On Wed, Mar 7, 2018 at 2:20 AM, "Ingo Althöfer" <3-hirn-ver...@gmx.de> wrote: > Hi D

Re: [Computer-go] 9x9 is last frontier?

louts" means precisely. Can you either describe them or give > me a reference? > > Thanks, > Álvaro. > > > > On Tue, Mar 6, 2018 at 1:49 PM, Dan <dsha...@gmail.com> wrote: > >> I did a quick test with my MCTS chess engine wth two different >> implemen

Re: [Computer-go] 9x9 is last frontier?

scorpio-pmcts: 41 - 1 - 2 [0.955] 44 Elo difference: 528.89 +/- nan scorpio-mcts uses alpha-beta rollouts scorpio-pmcts is "pure" mcts with averaging and UCB formula. Daniel On Tue, Mar 6, 2018 at 11:46 AM, Dan <dsha...@gmail.com> wrote: > I am pretty sure it is an MCTS pr

Re: [Computer-go] 9x9 is last frontier?

this policy trains both search and evaluation to be internally > consistent? The policy head is trained to refute the bad moves that will > come up in search, and the value head is trained to the value observed by > the full tree. > > > > *From:* Computer-go [mailto:computer-go-boun...@c

Re: [Computer-go] 9x9 is last frontier?

that is full of traps. I m not surprised Lela zero did well in go. On Mon, Mar 5, 2018 at 2:16 AM Gian-Carlo Pascutto <g...@sjeng.org> wrote: > On 02-03-18 17:07, Dan wrote: > > Leela-chess is not performing well enough > > I don't understand how one can say that gi

Re: [Computer-go] 9x9 is last frontier?

AM, Xavier Combelle <xavier.combe...@gmail.com> wrote: > Where is leela chess. How many games it is trained on? > > Le 2 mars 2018 18:20, "Dan" <dsha...@gmail.com> a écrit : > >> Hello Aja, >> >> Could you enlighten me on how AlphaZero handles

Re: [Computer-go] 9x9 is last frontier?

Hello Aja, Could you enlighten me on how AlphaZero handles tactics in chess ? It seems the mcts approach as described in the paper does not perform well enough. Leela-chess is not performing well enough even though leela-go seems to be doing well. Daniel On Fri, Mar 2, 2018 at 4:52 AM,

Re: [Computer-go] MCTS with win-draw-loss scores

1 for must-win, or -1/3 for 3/1/0, or 1 for only-need-not-lose, > etc. > > Then just play games with a variety of values for this parameter in your > self-play training pipeline so the policy net gets exposed to each kind of > game. > > On Feb 13, 2018 10:40 AM, "Dan Schmid

Re: [Computer-go] MCTS with win-draw-loss scores

The AlphaZero paper says that they just assign values 1, 0, and -1 to wins, draws, and losses respectively. This is fine for maximizing your expected value over an infinite number of games given the way that chess tournaments (to pick the example that I'm familiar with) are typically scored, where

Re: [Computer-go] Mcts and tactics

-- > De : computer-go-requ...@computer-go.org > Date : 20/12/2017 01:57 (GMT+01:00) > À : computer-go@computer-go.org > Objet : Computer-go Digest, Vol 95, Issue 24 > > > Message: 1 > Date: Tue, 19 Dec 2017 16:26:00 -0700 > From: Dan <dsha...@gmail.com> > To:

[Computer-go] mcts and tactics

Hello all, It is known that MCTS's week point is tactics. How is AlphaZero able to resolve Go tactics such as ladders efficiently? If I recall correctly many people were asking the same question during the Lee Sedo match -- and it seemed it didn't have any problem with ladders and such. In chess

Re: [Computer-go] AlphaGo Zero

find it if you Google for "artificial intelligence existential threat". But the subject seems off-topic here. Dan ___ Computer-go mailing list Computer-go@computer-go.org http://computer-go.org/mailman/listinfo/computer-go

Re: [Computer-go] computergo.org domain

Joshua was referring to computergo.org; the email list is on computer-go.org . Dan On Tue, Sep 27, 2016 at 11:26 AM, Jim O'Flaherty <jim.oflaherty...@gmail.com > wrote: > Are you implying this email list will stop functioning if this domain > isn't renewed? > > On Tue, Sep 27

Re: [Computer-go] Having an "estimated winrate" on the AGA pro game broadcasts

ay on both sides. Crazy Stone reports an evaluation (like B+3.5) and confidence though it cautions against taking it too seriously. My assumption is that it's something like the median result, and standard deviation, of all the MCTS playouts. I find this more useful than the win rate it prov

Re: [Computer-go] Nice graph

How did they do it ? Is there a video of the presentation somewhere ? Thanks On Fri, Mar 25, 2016 at 5:59 PM, David Ongaro wrote: > That would mean 3 stones if the "4 stone handicap" has the same definition > as in the paper (7.5 Komi for white and 3 extra moves for

Re: [computer-go] Publishing source for (yet another) MC simulator

. exploitation ratios/patterns/generalization techniques. /Dan Anderson ___ computer-go mailing list computer-go@computer-go.org http://www.computer-go.org/mailman/listinfo/computer-go/

Re: [computer-go] Publishing source for (yet another) MC simulator

Don Dailey skrev: On Tue, 2008-11-04 at 20:13 +0100, Dan Andersson wrote: If one takes the position that bugs have a pretty significant impact on the strength of a program (A position I agree with) one could be pretty forgiving about the speed of execution of an algorithm if it is written

Re: [computer-go] programming languages

than C :) There is however a new kid on the block that is pretty impressive and manages to beat C/C++. ATS (Applied Type System) also emits C but due to the structure and type system the code is pretty specialized and optimized to beat any sane and optimized C program. /Dan I have noticed

Re: [computer-go] Re: Strength of Monte-Carlo w/ UCT...

and higher confidence. I could believe that they have a proof that the algorithm is scalable in computing power... but not necessarily that it is scalable against the problem of beating a human. MC/UCT is provably scalable up to perfect play. /Dan Andersson Firstly.. I don't know

[computer-go] KGS hoover perl script and related bash scripts

Hi, I have written a perl program that plays Go (poorly). It uses pattern matching. Patterns are automatically read into a database from sgf files. I will release the source code soon, but first here are some tools that can be used to download and extract games from KGS. They are acceptable to

[computer-go] an idea for a new measure of a computer go program's rank.

chosen by the program. For example a random point playing program could choose time limits of half a second per move, sudden death. Therefore I suggest that a program's strength can (if needed) be expressed as the shortest time limits that a player of a standard strength (eg Pro. 1 dan) would