Statistical Reinforcement Learning: Modern Machine Learning Approaches (by Masashi Sugiyama)


Author(s): Masashi Sugiyama

Publisher: Chapman and Hall/CRC
Publish date: 2015-03-26
ISBN-10: 1439856893
ISBN-13: 9781439856895
Language: English
Description:
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.

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