NetNews Usenet Archive 1992 #20/NN_1992_20.iso/spool/comp/ai/neuraln/3452

Internet Message Format | 1992-09-10 | 1.9 KB

Path: sparky!uunet!nestroy.wu-wien.ac.at!exaib.wu-wien.ac.at!bruhn
From: [e-mail] (Peter Bruhn)
Newsgroups: comp.ai.neural-nets
Subject: NNs in chess or other games
Date: 11 Sep 1992 10:36:40 GMT
Organization: Vienna University of Economics and Business Administration
Lines: 25
Sender: [e-mail] ( Peter Bruhn )
Distribution: world
Message-ID: <[e-mail]>
NNTP-Posting-Host: exaib.wu-wien.ac.at

Does anyone of you know something about an application of neural nets
in strategic games (esp. chess). What I think about is that a NN could
be trained to evaluate a position or some aspects of a position (e.g.
the structure of your pawns, how safe is the position of your king,...).

The idea behind is that evaluating a position is (as I see it) closely
related to pattern-recognition. An experienced human chess player is
able to identify a position as weak, even though there are no tactical
dangers to perceive and he/she has not seen the position before. So how
does he/she know? I think it is due to pattern recognition: He/She has
seen similiar positions before or has made the experience that a certain
pawn structure is a weak point. Once a chess master (I don't remember his
name) was asked how many moves he prefigures in advance and he answered
"normally: none". Even though this is an exageration, of course, his
answer shows that it is more important to be able to evaluate a position
than to prefigure a lot of moves! Interestingly todays chess programs
take the other way: the use brute force! And this is the reason why
computers are good in chess, but not in games like Go. In Go there are
more possibilities and brute force will not work so well. So what I
think is that we should put more emphasis on the evaluation of positions
(of a game) rather than on brute force. And maybe NNs could help !?

Any comments are appreciated!

Peter ([e-mail])