Author: Robert Hyatt
Date: 05:09:12 06/02/98
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On June 02, 1998 at 03:21:38, Stuart Cracraft wrote: >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 all you have to do is write the hash entry out when the score drops, and reload it before each move from then on, or (as I do) load them once and flag them as "permanent". That is all you do. Hashing will take care of the rest, and you will see the "trouble" several plies earlier the next time you play the same game, and you will play a different move to avoid reaching the position where the score is going to drop.
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