Author: Dann Corbit
Date: 13:24:42 04/09/04
I have been thinking about forward pruning. (Did you smell wood burning?) The ten cent description of Baysian logic to those who have not examined it: As more information comes in, we revise our probability estimates. The Monty Hall problem is an excellent example of it. Anyway, when you look at the techniques used to decide whether or not to exercise some sort of forward pruning that are not complete no-brainers like Alpha-Beta cutoffs, it seems logical to me to employ Baysian logic. The reason is that advancing search depths give increased information. It seems a perfect fit for the theory. It seems to me it could even be used with a notion like: Given the large number of available moves and the huge negative score, do we even need to verify this null move? And things of that nature. Has anyone tried it?
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