> > > The basic explanation for why this is not straightforward is that you > never want your program to consider moves in the direction of > low-probability wins, no matter how large margins they might have; the > MC measurement function is very noisy with regards to individual samples. >
I do wonder though whether a final score value network would work better than MC here, and whether there could be a minimum win percentage threshold that could work. I'd love to see someone implement a final score value network and chose moves according to expected score or expected value (expected winning percentage * expected final score), with a minimum filter for expected winning percentage.
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