On Fri, Oct 28, 2011 at 02:02:28PM -0700, Dave Dyer wrote:
>
> >You have missed a key point. UCT is an ideal framework for integrating many
> >potentially incomplete, contradictory, or even potentially wrong, knowledge
> >sources. There are a zillion ways to add knowledge, and UCT guarantees that
> >you won't pay an asymptotic price.
>
>
> With random playouts, there is no place to add knowledge.
Huh, what about node priors?
> With heavier playouts, the "signal" from the win rate can still
> be very weak, or even wrong.
Of course, if it couldn't be wrong, we would have perfect programs. :)
My experience is that RAVE biases moves by knowledge much more strongly
than UCT, since frequent heavy playout choices are greatly magnified.
> UCT is particularly weak when a timely move is required - making the
> correct move 2 moves later looks 99% as good as making it immediately.
I can't remember hitting anything like that much.
It ain't always easy to integrate knowledge in UCT, but while I don't
have much practical experience with other game tree search algorithms,
I'd imagine it's even trickier with the classic evaluation function
approach.
--
Petr "Pasky" Baudis
We live on an island surrounded by a sea of ignorance. As our island
of knowledge grows, so does the shore of our ignorace. -- J. A. Wheeler
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