Author: blass uri
Date: 08:42:24 08/01/98
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On July 31, 1998 at 18:07:57, Don Dailey wrote: >Amir gave a formula a while back for converting a score to a >probability. This formula works very well once you have chosen >the right constant. Here is the equation he gave: > >expectancy = 1/(1 + exp(-score/K)) You can take all the positions from games of the best players in correspondence chess, evaluate K for every program and translate the evaluation to expectancy. After that you can compute the mean of squares of the differnce between the expectation and the real result of the game for every program. The program with the lower average is probably the program with the best positional understanding. It is interesting to do this test to the top programs. Uri > >where K is some constant and score is a score returned by your >chess program (in terms of pawns in our case.) A value of K near >120 seems to be about right for Cilkchess, at least when it comes >to predicting the results of master games. > >In case you are interested, the inverse of this formula is: > > score = -K * log( (1-expectancy)/expectancy ) > > > >- Don
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