Adaptive Representations for Reinforcement Learning
This book presents new algorithms for reinforcement learning, a form of machine learning in which an autonomous agent seeks a control policy for a sequential decision task. Since current methods typically rely on manually designed solution representations, agents that automatically adapt their own r...
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Format: | Electronic eBook |
Language: | English |
Published: |
Berlin, Heidelberg :
Springer Berlin Heidelberg,
2010.
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Series: | Studies in Computational Intelligence,
291 |
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Online Access: | Full Text via HEAL-Link |
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