Author: Stuart Cracraft
Date: 00:21:38 06/02/98
So what I hear is that having position-based "learning" is something like saving the position after a really bad drop in the iteration of a score in the hash table with a special flag. When the game ends, write out all such entries to a disk based file. When restarting the program, read in the disk based file into the hash table and set the flags. When searching, if the position turns out to be one of those positions, then what? I could dig out my Slate (one or the other forgot which) article in ICCA on the "Mouse" program -- is that essentially what this Position-Based "Learning" is that some programmers are using to create artificial wins against other programs? If so, any big refinements to Slate's method for the current crop? If no, what are the major differences between Slate's method and the current vogue? Thanks, --Stuart
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