Author: José Antônio Fabiano Mendes
Date: 07:16:00 10/11/00
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On October 11, 2000 at 05:40:43, Graham Laight wrote: >On October 10, 2000 at 20:56:58, Michael Neish wrote: > >> >>Hello, >> >>I'd like to learn a little about pattern recognition as applied to Chess, and >>would like to ask whether anyone could direct me to some information either >>online or in the literature, or has first-hand experience at this sort of >>programming (or knowledge), and would like to comment about it. >> >>All I've heard up to now is that techniques like genetic algorithms and neural >>networks fail woefully at Chess. >> >>Well, I got tired of trying to etch the same path as everyone else is (null >>move, mobility scores, hash tables ... ) and have decided to try something >>different. Please forgive my naivety. :) >> >>Cheers, >> >>Mike. > >Good thinking, Mike! > >Whatever you do, don't let the people here discourage you. When you ask to >discuss this kind of thing, you tend to get a lot of "can't be done", "not in >our lifetime", and other such ill thought out remarks. > >Well the fact is that most people in the chess community have dedicated their >lives to the fast search method, and are not willing to countenance the >possibility of alternative ways. One famous science author (can't remember his >name, but it's from his book "The red Queen") said that science does not usually >advance until the people in charge, who believe in the prevailing doctrine, die. > >You know what I say? Of course NNs can recognise patterns - that's EXACTLY what >they do well! Nobody has done it yet for chess - but if NN chess pattern >recognition had received as much study as fast searching has, I think it would >be doing it well by now. > >Genetic algorithms? > >Yes - with some imagination these could be used as well. If you make a selection >of "components" for evaluating chess positions, a genetic algorithm might be >able to both select the best combination of components and tune them to make the >computer evaluate positions to the satisfaction of a strong player. > >My suggestion has always been to select among (a database of) different >evaluation functions, depending on the current position. > >Whatever you do in the knowledge arena, you're going to pay a high price in >terms of NPS. Human NPS is probably about 2 to 4. > >Given the persistent weaknesses of today's strongest programs, there could be >rich rewards for the individual or team that addresses these issues. > >links to get you started: > >http://forum.swarthmore.edu/~jay/learn-game/systems/neurochess.html >http://forum.swarthmore.edu/~jay/learn-game/systems/sal.html http://www-formal.stanford.edu/jmc/chess.html JAFM
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