Author: Scott Gasch
Date: 15:08:35 11/01/99
I was reading a book on AI the other day and, out of curiousity, skimmed over to
the game programming area. I was surprised to find a strange (?) idea about how
to write an eval routine mentioned.
As best I understand it, this eval method assigns scores of -1, 0 or 1 to some
position features (e.g. material, mobility, whatever...) and -2, -1, 0, 1, 2 to
others. Then it combines related features into a "set". Like, I guess, it
might combine, say, knight-attacks, rook-attacks, pawn-attacks etc... into one
set. The set consists of one feature that has five steps of resolution and
others that have only three. So the end set might look like { -2, -1, -1, 0,
-1} for instance. This set's values are then used to index a heirarchy of
tables that give the value of this configuration.
My questions are: 1) why is this a good idea? It seems like a waste of memory
(to store the tables) and it seems like it would be less accurate than a sum of
weighted terms style eval. 2) is anyone doing this or something
related/non-standard in their eval?
Scott
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