> My question is what is the best way to train these networks? My > current strategy is to do nothing until the game is over. I'll use a > static algorithm to reliably score the end game state. Then I'll > create a training corpus by taking the score and iterating through > each move in the game, creating training sets in the form of > [boardstate, finalscore].
I think you'll run into problems with this training strategy; is each move worth the final score?. You might want to look at TD-Lambda, Q-learning or Sarsa algorithms. See the book on "Reinforcement Learning" by Sutton and Barto. it's online at : http://www.cs.ualberta.ca/%7Esutton/book/ebook/the-book.html some work by IBM using TD-Lambda to train an ANN to play backgammon: http://www.research.ibm.com/massive/tdl.html regards Matt -- Dr Matthew Studley Artificial Intelligence Group Faculty of Computer Science, Engineering and Mathematics University of the West of England Coldharbour Lane Frenchay Bristol UK BS16 1QY ================================= tel: +44 (0) 11732 83177 mob: +44 (0) 7712 659022 This email was independently scanned for viruses by McAfee anti-virus software and none were found _______________________________________________ Pyro-users mailing list [email protected] http://emergent.brynmawr.edu/mailman/listinfo/pyro-users
