David Fotland wrote: > I've thought about using mcts for Arimaa, and it might be better than > alpha-beta. Arimaa has a huge branching factor, and since the pieces move > slowly, human long-term planning works well against computers. Mcts prunes > better, so it should get deeper PVs. AMAF might help too, since in a long > plan it is often not critical what order the moves are in. > > Someone should give it a try. > >> David, is MCTS likely to be useful for Arimaa? >> >> Darren >>
Jeff Bacher author of Clueless gave UCT w/light playouts a try a few years ago but without much success. If I'm remembering correctly it played fairly decent in the end game, but for most of the game was much to prone to advancing rabbits on the off chance that they could sneak through. I also gave UCT a bit of a try but never got it playing much better than a 1 ply static evaluation. If I can get my alpha-beta program up to the same level as yours I would like to go explore MCTS and other search methods some more. There have been a number of new programs in development this year but I'm not aware of any of the ones that have made it to the stage of actually playing games being anything other than alpha-beta. Janzert _______________________________________________ computer-go mailing list computer-go@computer-go.org http://www.computer-go.org/mailman/listinfo/computer-go/
