Author: Robert Hyatt
Date: 19:23:00 02/15/03
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On February 15, 2003 at 08:29:54, martin fierz wrote: >i was thinking of implementing position learning in my checkers program, and was >trying to find out how this is typically done. if i understand it properly, >here's what people do: > >1) if the search returns a value much lower than the previous search (define >"much lower" as you like), write this position with it's value to the learn-file >on disk. >2) before every search, stuff positions from the learn file in the hashtable. > >this all sounds sensible to me, and i can see that this helps. however, i have a >stupid question about it. let's imagine that in the initial position A your >program is worse and decides to sac some material for a last-chance attack. a >few moves later, in position B, it may think that it's compensation is not >sufficient and drop it's score and learn this position. another 2 moves later it >suddenly sees that it has a perpetual check, and that the move in position A was >not to blame at all. i think this scenario is not quite unrealistic, and it >seems to me that position learning doesnt work here, because you only learn that >position B was bad (when in fact it wasn't). even if you were writing ALL >positions to disk after searching them (something i would like to do in >checkers), then you still haven't solved the problem: in your next search at >position A you will have a hash hit at position B telling you that the correct >move is bad, because you can't see further than your hash hit. > >hmmm. is there any workaround for this? > >cheers > martin This is a well-known issue, and I should add that position learning doesn't claim to solve everything. It is really a defense against repeating the same game multiple times which humans have been known to do. But as you notice, it will not solve every kind of position, because of local maxima issues. IE there are some holes you can not climb out because to do so means you first have to go for a _lower_ score, to reach the valley floor and start to climb up the other side...
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