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iGore

ANN w/ Reinforcement Learning

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Does anyone have example/source code for a reinforcement learning algorithm that utilizes neural networks? I have been researching this for quite some time on the internet and all of the sources I have found are either very mathematical and theoritical instead of implementory or are absolutely incomprehensible. Bridging the gap between math equations to computer code has been difficult (partial derivatives and gradients) so working example code would be a godsend. I already have an instance of a supervised training back-propagating NN so I am familiar with the networks themselves. I'm dying to find an example of the weight-changing equation in a program that works. Thanks for the assitance! [Edited by - iGore on November 27, 2004 3:26:58 PM]

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Try looking for Gerald Tesauro's TD-Gammon. It's a famous backgammon algorithm that uses temporal difference reinforcement learning combined with a feed forward neural network. If you have a backpropogation algorithm, then training is as simple as calculating the error between your network's output and the reward received by the agent. If you are using temporal difference learning, the reward will be the agent's immediate reward plus the discounted expected reward of the next state-action pair the agent encounters. Your network error is the difference between your network output and this reward. Just train your network using this error and you should be good to go.

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