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...
| প্রধান লেখক: | , |
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| অন্যান্য লেখক: | |
| বিন্যাস: | প্রবন্ধ |
| ভাষা: | en_US |
| প্রকাশিত: |
Institute of Electrical and Electronics Engineers
2010
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| অনলাইন ব্যবহার করুন: | http://hdl.handle.net/1721.1/58907 https://orcid.org/0000-0001-8576-1930 |