Two things explains this result: a) the neuralnet is not perfect and hence the luck evaluation is not perfect. For example consider a really bad neuralnet that always returned an equity of zero. The luck would be evaluated as zero as well. The luck evaluation is constructed in a way that ensures zero bias in an infinite number of games, but not in a single game.
b) The summed luck is 1.133 point (in a perfect world this number would be 1) which means that Blue has gained 1.133 point by luck (his luck and whites bad luck here) and white has lost 1.133 (his bad luck and Blues good luck here). In reality Blue won one point and his luck adjusted result is -0.133 pont (0 in a perfect world). White lost one point and his luck adjusted result is 0.133 (also 0 in a perfect world). If you set 0-ply to play against 2-ply in a high number of 1-point matches you should see that the summed luck averaged by the number of games is zero but that the Luck adjusted result averaged by the number of matches is not zero. Hope this explains your observations. Christian. > Luck total EMG (Points) +0.270 ( +0.270) -0.863 > ( -0.863) > Actual result +1.000 -1.000 > > Luck adjusted result -0.133 +0.133 > > > > Cheers, > Ian Shaw > > _______________________________________________ > Bug-gnubg mailing list > [email protected] > http://lists.gnu.org/mailman/listinfo/bug-gnubg > _______________________________________________ Bug-gnubg mailing list [email protected] http://lists.gnu.org/mailman/listinfo/bug-gnubg
