Re: computer-go: Learning from existing games

[Erik van der Werf <E.vanderWerf@xxxxxxxxxxxxx>]

Frank Steinmann wrote:
> 
> Hello,
> 
> 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
> ;-) )?
> 
> Frank

Yes, there are several ways. I suggest you start reading the literature
on Supervised Learning and Reinforcement Learning. Also take a look at
the papers written explicitly about Computer Go. Markus Enzenbergers
list is a good place to start.

http://www.markus-enzenberger.de/compgo_biblio.html

Erik