Q-learning and policy iteration algorithms for stochastic shortest path problems

We consider the stochastic shortest path problem, a classical finite-state Markovian decision problem with a termination state, and we propose new convergent Q-learning algorithms that combine elements of policy iteration and classical Q-learning/value iteration. These algorithms are related to the...

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Bibliographic Details
Main Authors: Yu, Huizhen (Contributor), Bertsekas, Dimitri P. (Contributor)
Other Authors: Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor), Massachusetts Institute of Technology. Laboratory for Information and Decision Systems (Contributor)
Format: Article
Language:English
Published: Springer-Verlag, 2015-02-03T19:29:00Z.
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