Dear Bob,
thanks for your explanations. Now I see clearer.
> First, the title is deliberately provocative.
Accepted.
> Also, though, the talk is not just about go: some of it is about
> formally undecidable games, that computers provably can't play
> well (and of course, that humans can't either!).
I see.
How much sense does it make to think about Monte-Carlo approaches
to certain games that are undecidable? (Probably it does make a lot
of sense in certain cases.)
> Surprisingly, some of these games can be played with
> finite physical resources (unlike, say, an infinite Turing-machine
> tape). One real game that is a good candidate for being undecidable
> (though it hasn't been proven) is Rengo Kriegspiel: team blindfold go.
Here, indeed Monte-Carlo might "work" - for instance against
opponents with limited capabilities.
*********************
When I read your original mail the following three main
steps of game tree search came to my mind:
(i) Zermelo's basic tree approach (with minimaxing) in 1911 or 1912.
(ii) Shannon's paper from 1950 with the proposal to prune the (large)
tree and to evaluate the artificial leaves by heuristic values.
(iii) The Monte Carlo approach: getting an evaluation for a position
not by applying a heuristic but
by playing many "random" games from this position till the very end.
These three mile-stones in mind, there are not many games left, where
computers are really weak.
Ingo.
PS: When you meet Elwyn Berlekamp in the symposium you may tell
him that looking at the game Clobber in the 2002-Dagstuhl workshop
(where he was one of the organizers and I one of the participants)
was my starting point for becoming a "game designer with computer help"
and thus indrectly the starting point for me to investigate Monte Carlo,
first in games with random elements.
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