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...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
Springer-Verlag
2015
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| Online Access: | http://hdl.handle.net/1721.1/93745 https://orcid.org/0000-0001-6909-7208 |