Author: José Carlos
Date: 09:57:40 05/06/99
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On May 06, 1999 at 12:48:54, José de Jesús García Ruvalcaba wrote: >On May 06, 1999 at 11:34:51, José Carlos wrote: > >> I'm finishing writing the first beta version of my chess program (Averno). It >>is quite simple at this moment, but I always try to be original, and I have an >>idea about the eval function: >> Instead of "inventing" rules for evaluating positions from my experience in >>chess (or others experience), could it be possible to make the program invent by >>itself those rules? I mean, if I was able to write some code for, starting with >>a position, an evaluation (taken from grandmasters games) and a best move, the >>program could "inference" (sorry, I dont know this word in english correctly, >>but I hope you understand) some rules that he, later, use in his games. >> How? Well, there are many interesting AI methods to do this. I'm particularly >>interested in Neural Networks, but some others may be suggested. >> >> Have any of you thought of this any time? Any ideas? Any real cases? >> >> Regards. >> >> José C. > > Deep Blue's evaluation was tuned automatically, the weigths of the terms of the >evaluation function were solved by a least squares method, trying to reproduce >the moves of the winning side of a few thousands grandmaster games. > What I do not like about Deep Blue's method is that winning a game against a >grandmaster is not a guarantee of playing only good moves in that game. > I would like to see a program that actually invents the terms of the evaluation >function, then checks if they are actually relevant, and finally weigths them; >and in a more rational way than the Deep Blue method. >José J. Correct. Least squares method inplies that someone decided the terms of the function, and the programs only weigths them. I agree with you, that it would be more interesting that the program could "invent" those terms itself. That's what I'm trying to do for my program. José C.
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