On Wed, Jun 29, 2011 at 4:31 PM, Hendrik Baier <[email protected] > wrote:
> It sounds crazy to me that it works at all as it has no real knowledge of >> the position. >> > > It sounds crazy indeed. But your typical MCTS (without node priors) has no > knowledge of positions at all - it just learns which of the available > actions seem to work best. The classifier actually has more knowledge than a > typical MCTS tree, since it generalizes between positions, as you said. And > it generalizes based on the intuition that good reactions to the same moves > are often useful in many branches of the search tree, see our Power of > Forgetting paper. > I'm interested in integrating this neural network approach into MCTS such > that the convergence properties of MCTS are not lost... > > By the way, as far as I understand the network is not built from scratch > before each move, but before each game. Each move could be an interesting > approach as well (maybe for longer time settings?). > Although I said "before each move", what I really understood was that it was NOT pre-computed. When I said it sounds crazy of course I wasn't being critical, I accept that it is an interesting experiment. Years ago I did some experiments with MCTS that tried to generalized and played some games on KGS. The program was weak but I got some interesting comments about it because several players commented that it seemed to understand the positions well but sucked at technique. I don't remember the exact details but I tried to treat patterns more like moves while still using tree search. I have long felt that computer Go needed better ways to generalize knowledge learned during the search and/or playouts. Don > ______________________________**_________________ > Computer-go mailing list > [email protected] > http://dvandva.org/cgi-bin/**mailman/listinfo/computer-go<http://dvandva.org/cgi-bin/mailman/listinfo/computer-go> >
_______________________________________________ Computer-go mailing list [email protected] http://dvandva.org/cgi-bin/mailman/listinfo/computer-go
