Action selection in modular reinforcement learning
Modular reinforcement learning is an approach to resolve the curse of dimensionality problem in traditional reinforcement learning. We design and implement a modular reinforcement learning algorithm, which is based on three major components: Markov decision process decomposition, module training, an...
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| Format: | Others |
| Language: | en |
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2014
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| Online Access: | http://hdl.handle.net/2152/25916 |