An expectation maximization algorithm for continuous Markov decision processes with arbitrary rewards
We derive a new expectation maximization algorithm for policy optimization in linear Gaussian Markov decision processes, where the reward function is parameterized in terms of a flexible mixture of Gaussians. This approach exploits both analytical tractability and numerical optimization. Consequentl...
| Hauptverfasser: | , , , |
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| Format: | Journal article |
| Sprache: | English |
| Veröffentlicht: |
2009
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