Computer Chess Club Archives




Subject: Re: chess and neural networks

Author: Marc van Hal

Date: 14:08:29 07/01/03

Go up one level in this thread

On July 01, 2003 at 16:17:37, Magoo wrote:

>On July 01, 2003 at 16:02:14, Albert Bertilsson wrote:
>>On July 01, 2003 at 15:55:07, Anthony Cozzie wrote:
>>>On July 01, 2003 at 15:42:42, Albert Bertilsson wrote:
>>>>>Yes, but things are different with chess. In backgammon, you don't need to do
>>>>>deep searches. Backgammon is a randomized game, chess is not. There have been
>>>>>attempts, but not that succesful, i have looked at KnightCap, which uses
>>>>>standard minimax with a ANN to evaluate the quiet positions.It has a rating of
>>>>>about 2200 at FICS... pretty good, but no way near the top. I guess a program
>>>>>with minimax only counting material would have a rating near that. Like they
>>>>>say, chess is 99% Tactics. Nothing beats deeper searching.
>>>>2200 on FICS with MiniMax counting material only?
>>>>That is crazy!
>>>>One of us is wrong, and hope it isn't me because I've spent many hours on my
>>>>engine and it still is now way near 2200 in anything other than Lightning! If
>>>>you're right I'm probably the worst chess programmer ever, or have missunderstod
>>>>your message completely.
>>>>/Regards Albert
>>>Your engine, being new, still has a lot of bugs.  I'm not trying to insult you;
>>>it took me a full year to get my transposition table right.   At least, I think
>>>its right. Maybe.  Anyway, the point is that it takes quite a while to get a
>>>good framework. I suspect on ICC a program with PST evaluation only could get
>>>2200 blitz. (with material evaluation only it would play the opening horribly,
>>>e.g. Nc3-b1-c3-b1-c3 oh darn I lose my queen sort of stuff)
>>I agree that PST evaluation with Alpha-Beta and a transposition-table can play
>>at least decent chess, but that's quite many powerful improvements over MiniMax
>>with Material only.
>>/Regards Albert
>I said near, and when i say minimax, i really mean alphabeta (no one uses a
>straightforward minimax). When my engine was "born" (minimardi) it had only
>material evaluation, searching 4 ply, it could play a decent game. Rated around
>1700 blitz at FICS. Now, consider searching around 8 ply, i think a rating >2000
>is not hard to imagine. My point was that in chess, the most important thing to
>accuretly evaluate positions is a deep search. No matter what methods you use,
>if you search deep your program will play decent. This is one of the reasons why
>ANN have worked so well in backgammon and not in chess.

Can't neural networks look deep ?
Why is that?
And do neural networks learn or not?


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