A thought about that impressive article: Move prediction has become the bot workhorse. But I have a question: how can those predictions work, without having a goal? The predictions are obviously purely shape based, so a 41% success rate is really pretty awesome. But that means that some positions, like running battles, the percentages will be a lot better than in others, like non eye-stealing eye filling. How about giving the learning algorithms a "hint" about the solution? Not about the area, but the type of move. So when, for example, in the tree, certain stones end up captured a lot, a different move predictor, that prefers taking libs, filling eyes ect might try to avoid that fate. I know this is pure handwaving, but some kind of feedback from search results to predictor used seems needed.
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