Optimization-based Approximate Dynamic Programming
Reinforcement learning algorithms hold promise in many complex domains, such as resource management and planning under uncertainty. Most reinforcement learning algorithms are iterative - they successively approximate the solution based on a set of samples and features. Although these iterative algor...
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| Format: | Others |
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ScholarWorks@UMass Amherst
2010
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| Online Access: | https://scholarworks.umass.edu/open_access_dissertations/308 https://scholarworks.umass.edu/cgi/viewcontent.cgi?article=1302&context=open_access_dissertations |