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- Newsgroups: comp.ai.neural-nets
- Path: sparky!uunet!stanford.edu!leland.Stanford.EDU!northstar!ed
- From: ed@northstar.Stanford.EDU (Edward Wilson)
- Subject: Re: NNs in chess or other games
- Message-ID: <1992Sep14.170420.25041@leland.Stanford.EDU>
- Sender: ed@northstar (Edward Wilson)
- Organization: stanford
- Date: Mon, 14 Sep 92 17:04:20 GMT
- Lines: 30
-
-
- I remember reading an article (the cover article, I believe) in Scientific
- American ~2 years ago regarding chess-playing computers (at CMU ?).
-
- It did not involve
- NNs, but talked a lot about the computers and algorithms. One interesting
- graph I remember was one that had on the abscissa the number of moves ahead
- that the best chess computers were able to look ahead (the earliest ones were
- around 5 moves, and the latest ones were around 12-13 moves, I think). On
- the ordinate, they had the chess rating for the chess computer (ratings for
- chess players range from 1200 for beginners to 1800 for good players to 2300
- for "Masters" to ~2700 (?) for the handful of best players in the world).
- The interesting thing was that the graph, with ~10 data points was very linear -
- implying a direct relationship between how many moves the computer can look
- ahead and how good it is (ranking wise).
-
- At the time of the article, the best computers were able to beat all but the
- very best in the world (handful of people). I haven't heard anything since
- then, but it seemed at the time that it was just a matter of being able to look
- ahead about 2 or 3 more moves before the best could be beaten.
-
- On a related topic, you might want to check out some papers by Arthur Samuel
- (Bell Labs), one printed in MIT's Technology Review in 1959. He was working
- with slightly more primitive computers, so he worked on trying to *teach* a
- computer to play checkers. Teach is the key word here.
-
- Good luck, hope this helps.
-
- Ed Wilson, Aerospace Robotics Lab, Stanford University
- ed@sun-valley.stanford.edu
-