MCTS avoids evaluation. That is its main trick.
It also avoids subproblems like the plague. Atleast sofar.
I think you are absolutely right that in the end a program will need to be able
to define subproblems, their local status, and the conditions that will change
that status. The current switching behavior, that results when more than one
critical area exists, can only be described as thrashing. Computing power alone
will not solve this.
But local results don't stay local. And a winning move is often a winning move
because it influences several critcal areas at the same time, effectively
merging them.
How to apply divide and conquer to the protean and holistic game of go will
remain a headache for a long time.
Stefan
This may be useful in computer Go. One of the reasons human pros do well is
that they compute certain sub-problems once, and don't repeat the effort until
something important changes. They know in an instant that certain positions are
live or dead or seki; they know when a move ( reducing a liberty, for example )
disturbs that result. This could probably be emulated with theorem-proving
ability. Presently, search algorithms have to rediscover these results many
times over; this is (in my opinion) why computer programs get significantly
weaker when starved for time; they cannot think deeply enough to solve problems
which may be solved in an eyeblink by a pro.
Terry McIntyre terrymcint...@yahoo.com
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