Asynchronous Stochastic Approximation and Q-Learning |
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| Authors: | Tsitsiklis John N |
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| Affiliation: | (1) Laboratory for Information and Decision Systems, Massachusetts Institute of Technology, 02139 Cambridge, MA |
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| Abstract: | We provide some general results on the convergence of a class of stochastic approximation algorithms and their parallel and asynchronous variants. We then use these results to study the Q-learning algorithm, a reinforcement learning method for solving Markov decision problems, and establish its convergence under conditions more general than previously available. |
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| Keywords: | Reinforcement learning Q-learning dynamic programming stochastic approximation |
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