Greetings from a lurker,
Forgive me if I am talking out of my hat. It has been a long time
since I have done any real coding.
It seems most of the gains in MC/UCT come fairly quickly (or rather
you can get within 50% of a good move guess with a few iterations).
It would be interesting to perhaps do a progressive stepping down/
widening, i.e. 1k playouts with komi + 3 as the cutoff, then feed this
tree into 2k playouts with komi + 2, then 4k playouts with komi + 1,
and then finally do the usual full blown regular analysis, say 50k
playouts (numbers can be tweaked of course). You would lose the
initial simulations from your final one, so you would be sacrificing
say 10% of the possible simulations, but on the other hand it would
seem to bias the tree toward making moves that have a greater chance
of winning by a greedy amount without explicitly telling the computer
it has to win by a certain number, which would seem dangerous if the
simulations are near the threshold.
I apologize if this is an obvious idea, was just wondering if there
was a flaw with it/someone had done experiments in this direction
already.
-Brett
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