Exploring partially observable Markov decision processes by exploting structure and heuristic information
This thesis is about chance and choice, or decisions under uncertainty. The desire for creating an intelligent agent performing rewarding tasks in a realistic world urges for working models to do sequential decision making and planning. In responding to this grand wish, decision-theoretic plannin...
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| Format: | Others |
| Language: | English |
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2009
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| Online Access: | http://hdl.handle.net/2429/5772 |