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Statistical Reinforcement Learning: Modern Machine Learning Approaches

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Reinforcement learning (RL) is a framework for decision making in unknown environments based on a large amount of data. Several practical RL applications for business intelligence, plant control, and game players have been successfully explored in recent years. Providing an accessible introduction to the field, this book covers model-based and model-free approaches, policy iteration, and policy search methods. It presents illustrative examples and state-of-the-art results, including dimensionality reduction in RL and risk-sensitive RLm. The book provides a bridge between RL and data mining and machine learning research.


Request Code : ZLIBIO1324610
Categories:
Year:
2015
Edition:
1
Publisher:
Chapman and Hall/CRC
Language:
English
Pages:
573
ISBN 10:
1439856893
ISBN 13:
9781439856895
ISBN:
1439856893,9781439856895

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