[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

Re: computer-go: Learning from existing games



In message <003501c2bb22$145b38c0$416e8150@steinmann>, Frank Steinmann <frank-steinmann@xxxxxxxxxxxxxxxxx> writes

realizing, that my go program doesn't make any good moves at all (and is
also badly desinged), I decided to start again with a completly different
strategy. My program ist going to learn from existing games (and from the
ones it has played itself) now.

My question: To analyze a game, I'd like to evaluate the moves, that have
been made in that game. The simplest way to do that, is to give every move
the value of the game result (positive for the moves of the winner, negative
for the moves of the loser). But I don't think it is a very promising way,
because you don't consider that there could be some good moves and some bad
moves which finally lead to the game result. Are there any better ways to do
that (except from getting a game analysis from a professional go player
;-) )?
Bluntly, no.

If there were a simple way to tell a good move from a bad move, you would just implement it in your program, you wouldn't need the training strategy.

Nick
--
Nick Wedd nick@xxxxxxxxxxxxxxxxx