That's the beauty of MC! It really is a beautiful system. Initially, they were totally random playouts. But the more powerful MC Go engines do not do
completely random playouts; they do "heavy" playouts. But if you were to look at a heavy playout, it would still look like a very weak Go player's game. In
addition to heavy playouts, there is the tree aspect, which you did not mention. One way to catagorize and MC engine would be whether or not it is "MCTS" (MC
Tree Search). If so, it will play much stronger and can make statements about scalability. Pure MC does not use a tree.
Fred Hapgood wrote:
I have a really basic question about how MC works in the context of Go.
Suppose the problem is to make the first move in a game, and suppose we
have accepted as a constraint that we will abstain from just copying
some joseki out of a book -- we are going to use MC to figure out the
first move de novo. We turn on the software and it begins to play out
games. My question is: how does the software pick its first move? Does
it move entirely at random? Sometimes it sounds that way MC works is by
picking each move at random, from the first to the last, for a million
games or so. The trouble is that the number of possible Go games is so
large that a million games would not even begin to explore the
possibilities. It is hard to imagine anything useful emerging from
examining such a small number. So I'm guessing that the moves are not
chosen at random. But even if you reduce the possibilities to two
options per move, which would be pretty impressive, you'd still run out
of your million games in only twenty moves, after which you would be
back to picking at random again.
What am I missing??
http://www.BostonScienceAndEngineeringLectures.com
http://www.pobox.com/~fhapgood
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