Author: Robert Hyatt
Date: 16:35:30 11/01/99
Go up one level in this thread
On November 01, 1999 at 18:08:35, Scott Gasch wrote:
>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
The idea is fine in theory. But in practice, the number of 'elements in the
set' can be so large that the amount of memory required is very large. Many
do something similar (I compute a bunch of terms) but then do some combinational
stuff to end up with one final score, without resorting to a huge MXN array.
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