Author: Amir Ban
Date: 06:37:24 10/26/98
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On October 26, 1998 at 06:00:32, Jari Huikari wrote: >A newbie question again... > >My program has a fixed maximum thinking time. It uses iterative deepening. And >when thinkingtime=maximum time, it interrupts the search. If it was e.g. >interrupted during evaluating the move number 6, it uses the scores from >previous iteration for moves number 6 or higher, and for those five moves >calculated deeper than the others, I give a small bonus, because they are >deeper and better. > >Problem is that move ordering comes from alpha-beta search. The score of >the first move is an exact value for it, and the rest are upper bounds for >move values. > >Now if move number 1 turns to be bad in the deepest search, and time ends >just when it had been found, the program chooses another move. But it knows >only the UPPER BOUND of that. And the actual score may be much much worse... >and it can sometimes happen that program makes a very very ugly move. > >How should I handle this? > >(I have found one solution, but I think there must be better ways.) > > Jari I think you should give up the fixed time allocation and aim to do a full iteration, at least most of the time. Amir
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