Suppose an MC/NN program suggests a move with the supposedly highest
winning probability. Due to the imperfect information for suggesting
this move, I suggest to apply my human player principle "verify by
reading" by verifying the suggested move by reading. This can use the
following method "verification reading for probabilities", which I
suggest now:
We have the current position with a winning probability and the
suggested first move in the current position. Do _reading_ to quiet
leaves, for which we know or determine a winning probability. A decision
in the tree is a success iff it results in _at least_ the same
probability [alternative: a threshold probability] as that of the
current position.
I.e., the verification reading shall ensure that the winning probability
does not decrease as a consequence of starting with the suggested move.
Such should prevent the program from suddenly experiencing harshly
dropping probabilities during a few successive moves / mistakes of the
game, such as in game 4 of the AlphaGo - Lee Sedol match.
--
robert jasiek
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