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)
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 W
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 black after the
> first move.
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
'origine
> 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
> To: compute
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, Aja
AM, Xavier Combelle
wrote:
> Where is leela chess. How many games it is trained on?
>
> Le 2 mars 2018 18:20, "Dan" a écrit :
>
>> Hello Aja,
>>
>> Could you enlighten me on how AlphaZero handles tactics in chess ?
>>
>> It seems the mcts
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 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 given that they started with the
&
u see how 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:comput
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 wrote:
> I am pretty sure it is an MCTS problem and I suspect not s
s precisely. Can you either describe them or give
> me a reference?
>
> Thanks,
> Álvaro.
>
>
>
> On Tue, Mar 6, 2018 at 1:49 PM, Dan wrote:
>
>> I did a quick test with my MCTS chess engine wth two different
>> implementations.
>> A standard M
-beta 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:
>
ct play with higher 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
.. but this seems incredible to me.
No more incredible than that Mini-Max and Alpha-Beta will generate
perfect play given enough resources. In the worst case MC/UCT will build
a Mini-Max tree solving the game.
/Dan Andersson
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uly faster
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 not
runing/exploration v.
exploitation ratios/patterns/generalization techniques.
/Dan Anderson
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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
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
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 wrote:
> Are you implying this email list will stop functioning if this domain
> isn't renewed?
>
> On Tue, Sep 27, 2016 at 12:07 AM, J
for "artificial intelligence existential
threat". But the subject seems off-topic here.
Dan
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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
nly-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 Schmidt" wrote:
>
> The AlphaZero p
rting 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 intern
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
A is expected to beat B in a two-player match, B is expected
to beat C in a two-player match, and C is expected to beat A in a
two-player match.
So if the players are eccentric in that respect, a one-dimensional rating
system is always going to have real problems with accurate predictions.
Dan
O
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