Towards Global Reinforcement Learning
Sequential decision making under uncertainty is a ubiquitous problem. In everyday situations we are faced with a series of decisions that aim to maximize the probability of achieving some goal. However, decision outcomes are often uncertain and it is not always immediately evident how to determine i...
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| Language: | en |
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2008
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| Online Access: | http://hdl.handle.net/10012/3671 |