Statistical Reinforcement Learning: Modern Machine Learning Approaches (Chapman & Hall/CRC Machine Learning & Pattern Recognition)

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(as of Dec 07, 2024 22:25:10 UTC – Details)

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 gaming 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 RL. The book provides a bridge between RL and data mining and machine learning research.

ASIN ‏ : ‎ B08PW3CRNR
Publisher ‏ : ‎ Chapman and Hall/CRC; 1st edition (March 16, 2015)
Publication date ‏ : ‎ March 16, 2015
Language ‏ : ‎ English
File size ‏ : ‎ 9583 KB
Simultaneous device usage ‏ : ‎ Up to 4 simultaneous devices, per publisher limits
Text-to-Speech ‏ : ‎ Not enabled
Enhanced typesetting ‏ : ‎ Not Enabled
X-Ray ‏ : ‎ Not Enabled
Word Wise ‏ : ‎ Not Enabled
Print length ‏ : ‎ 206 pages
Format ‏ : ‎ Print Replica