But you can improve the prior probabilities of your search function by
remembering shapes (hopefully more abstract ones in the future,
including more knowledge about the neighbourhood) that seemed like good
moves before, so I don't share your opinion.
Whether or not this knowledge shout also be strongly employed deeper in
the search tree (corresponding to the "playout" part) is another
question to me.
Benjamin
I think trying to learn from human games is usually bad too, for similar
reasons. I had at least 3 reasons why I think it's bad, one of them is
simple what I call the omission problem, you don't really see (or
sample) the reasons certain moves are or are not played.
- Don
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