Learning methods in trick-taking card games
I'm looking for learning methods aplied to card trick-taking team games (bridge-like).
As so, it's:
a) NOT a two-player game
b) NOT a complete information games
-> minimax, alpha/beta prunning does not fit well. Adding Montecarlo would help a little, but that's not my problem just now.
c) NOT a war-like, strategic-like game
and most links don't apply.
I cannot see how Genetic/neural theory apllies in such kind of games because I'm stopped on how to evaluate "moves", strategy, ...
Actually my program (for a local card game) wins 46% games against humans (well, one human as ally and two human opponents), it plays ... mmm ... moderate, and I would like it to learn from history.
Any suggestions?
Thanks a lot
You may want to check out POKI, a poker playing agent that must deal with many of the challenges you are facing. http://www.cs.ualberta.ca/~games/poker/
The papers are your best bet for pertinant information but are very verbose. This is an active and challanging area of research.
The papers are your best bet for pertinant information but are very verbose. This is an active and challanging area of research.
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