Statistical Reinforcement Learning: Modern Machine Learning Approaches

✍ Scribed by Masashi Sugiyama

Publisher: Chapman and Hall/CRC
Year: 2015
Tongue: English
Leaves: 573
Edition: 1
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

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.

✦ Subjects

Информатика и вычислительная техника;Искусственный интеллект;

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