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glo
04-06-2007, 10:15 AM
Hi, me again, still trying to come up with a solution for Backgammon AI.

When I read about Gerald Tesauro's TDgammon (http://www.research.ibm.com/massive/tdl.html) - a backgammon AI implementation that can learn for itself yet can also play pretty well, I thought it'd be nice to dive into the subject and do something similar myself.

Wikipedia, just like other results in Google, had only shown me scattered information on puzzling subjects: Reinforcement Learning, Temporal Difference, TD(Lambda), Artificial Neural Networks, Feed-forward Backpropagation, Hidden Layers, etc. Unfortunately, being as thick as I am, I got quite lost in the land of terminology and couldn't put these little pieces together.
Apparently the water is deeper than I had hoped.

So any helpful tips on where do I begin, or how do I put it all together, would be greatly appreciated.

Happy_Reaper
04-06-2007, 10:11 PM
If I remember correctly, TDGammon use mostly temporal difference learning, so you'd really just want to look up on that.

glo
04-11-2007, 09:54 AM
Thanks, Happy_Reaper, I did manage to find an online book (http://www.cs.ualberta.ca/%7Esutton/book/ebook/the-book.html) that mentions TDGammon has also to do with neural networks (or back propagating multi layered perceptron network), so will try to see how the two work together.