Author: Artem Pyatakov
Date: 14:37:55 03/28/04
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Hi Uri, Thanks for the reply. I guess the same people who were active 3 years ago are still around :-) >>At the same time, any AI >>work has to compare itself with chess engine filled with excellent >>human-generated tricks, so it seems to perform poorly. >>Some examples: >>*ordering captures first during move ordering >>*check extensions >>*futility pruning > >I think futility pruning can be easily generalized for other games. >I also think that history based pruning and using history tables and killer >moves can be generalized for other games. Perhaps with Futility pruning you have a point, although I was talking more about the decision at which point to prune (in qsearch OR search and at what futility ranking OR maybe only when no checks are involved or whatever - these would be the tricks). Perhaps I was not very clear, but actually the history heuristic and the killer heuristic are examples of things that CAN be generalized to other games, which is why I focus my research on improving things such as the History heuristic and the Killer heuristic (I will post details in a different part of this threads under DETAILS) >I see no reason to replace alphabeta with something totally different. >Humans use alpha beta in every game and I see no reason to tell computers not to >use alphabeta and if they find that a move is bad to spend a lot of time on >trying to evaluate exactly how bad it is. Where are you getting the information that humans use Alpha-Beta in every game? There is some evidence of forward search in GM analysis, but the majority of the decisions are made on the pattern-recognition level, not with search. I have never seen any evidence of anything as sophisticated as alpha-beta being used by humans to play a game, and indeed many AI students find it very difficult to grasp at first exposure (including me). The reason I advocate keeping Alpha-Beta in my approach is simply because I think we are not ready to discard the whole framework and replace it with one giant simulation of a brain (neural network) or some giant genetic algorithm. More comments are always welcome, as they help me think about the problem. Artem
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