Statistical Reinforcement Learning: Modern Machine Learning Approaches (Chapman & Hall/CRC Machine Learning & Pattern Recognition)
By:
Sign Up Now!
Already a Member? Log In
You must be logged into UK education collection to access this title.
Learn about membership options,
or view our freely available titles.
- 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 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.
- Copyright:
- 2015
Book Details
- Book Quality:
- Publisher Quality
- Book Size:
- 206 Pages
- ISBN-13:
- 9781040058152
- Related ISBNs:
- 9780429105364, 9781439856901, 9780367575861, 9781439856895, 9781032708119
- Publisher:
- CRC Press
- Date of Addition:
- 06/27/24
- Copyrighted By:
- Taylor & Francis Group, LLC
- Adult content:
- No
- Language:
- English
- Has Image Descriptions:
- No
- Categories:
- Nonfiction, Computers and Internet, Business and Finance, Mathematics and Statistics
- Submitted By:
- Bookshare Staff
- Usage Restrictions:
- This is a copyrighted book.
Reviews
Other Books
- by Masashi Sugiyama
- in Nonfiction
- in Computers and Internet
- in Business and Finance
- in Mathematics and Statistics