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Subject: Re: Artificial Intelligence in Computer Chess

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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