Author: Jay Scott
Date: 19:17:02 02/25/98
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On February 25, 1998 at 18:09:58, Amir Ban wrote: >On February 25, 1998 at 16:54:55, Jay Scott wrote: > >> >>On February 25, 1998 at 05:09:41, Amir Ban wrote: >> >>>We all know what the BEST evaluation is. It's the one coming out of >>>perfect knowledge of the game. But what is good evaluation ? More >>>precisely, given two evaluation functions, how do you decide which is >>>better ? >> >>The question "which one is better?" is meaningless by itself. Better >>for what? >> > >Better for Computer Chess. Since this is the name of the newsgroup, I >thought I don't need to say that. Well, to me that still seems too vague to answer. Perhaps I am an unusually precise person. I imagine you mean something like better in practice for producing a strong chess program. In that case, all I can say is, you've got a darn good question! I don't think it's possible to fully separate the evaluation knowledge from the way it's used in the search. The two have to be tailored for each other. You can think of them separately, but you always have to consider how they interact as well. So maybe the answer is that there is no fully satisfactory way to decide other than playing games and seeing what happens. Lacking a theory of search, at least. :-/ In a narrow sense, this isn't surprising at all. Search is "what you do with knowledge", and knowledge by itself just sits there and does nothing. :-) It would be fascinatingly strange if all reasonable searches used knowledge the same, I think. >>[examples of ideas which I dismissed in the next sentence :-)] > >Right. I'm not so much interested in ideas that are dismissed in the >next sentence. I am looking for a formulation which at least someone >considers to be correct. The fact that it's not easy to find one is >surprising in itself. It shows that we don't have a good idea of what >what we are doing when we are busy "improving" our evaluation". Yes, I agree that this is surprising and shows our ignorance. I think there's plenty of room for new ideas in both the theory and the practice of combining search and knowledge. Jay
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