Approximate Dynamic Programming Using Bellman Residual Elimination and Gaussian Process Regression
This paper presents an approximate policy iteration algorithm for solving infinite-horizon, discounted Markov decision processes (MDPs) for which a model of the system is available. The algorithm is similar in spirit to Bellman residual minimization methods. However, by using Gaussian process regres...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
Institute of Electrical and Electronics Engineers,
2010-10-05T19:42:03Z.
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| Subjects: | |
| Online Access: | Get fulltext |