Hello John, Thank you for your interest.
Figure 3 in your UCT paper shows the accuracy of different simulation policies. Could you repeat these experiments for accuracy of win/loss determination only?
Actually the labelled positions are rather end game positions, and are labelled as 0/1 (loss/win). So we already are in the case you propose. BTW, experiments in actual play using the "best" simulation policy with RLGO (by "best" I mean giving the best MSE) has also been done (given in one table, I don't remember which) and showed the relevance of the MSE measure. (winning rate vs gnugo was around 9% against 8% with random simulation policy). Sylvain
So for each test position, you determine if it's won or lost under perfect play, and then see how close each policy gets to either 0% or 100% wins. One might think that this measure of accuracy is what actually matters to UCT, since it is not concerned with margin of victory. Is the advantage of Mogo's policy still as pronounced? regards, -John _______________________________________________ computer-go mailing list computer-go@computer-go.org http://www.computer-go.org/mailman/listinfo/computer-go/
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