My experience from doing search only with Valkyria, is that Go is not
different to Chess in the sense that each extra ply really makae a
difference. Improving evaluation almost always means that search gets
deeper in UCT-type programs. Monte-Carlo simulation + knowledge gives
a better signal. The question is what knowledge is needed and how to
effectively implement it such that search do not suffer but rather
improves.
-Magnus
Quoting Dave Dyer <[EMAIL PROTECTED]>:
I agree with your exposition of search as it applies to chess, but
I think there is a qualitative difference in Go.
In chess, evaluators can see clear progress, in the form of material
balance and statically determined positional factors, so each additional
ply gives you more opportunity to see progress.
Until Go evaluators give similarly strong and reliable signals, search
will be a very much weaker tool.
--
Magnus Persson
Berlin, Germany
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