Statistical Reinforcement Learning —— Modern Machine Learning Approaches

----- 统计强化学习：现代机器学习方法

ISBN: 9781439856895 出版年：2015 页码：206 Sugiyama, Masashi CRC Press

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.