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Can I read Multi-Agent Machine Learning : A Reinforcement Approach on EtoBox?
Multi-Agent Machine Learning : A Reinforcement Approach by HOWARD M.SCHWARTZ, Howard M Schwartz, Schwartz, H. M., H. M. Schwartz is a engineering available to read on EtoBox.
What is Multi-Agent Machine Learning : A Reinforcement Approach about?
<p>The book begins with a chapter on traditional methods of supervised learning, covering recursive least squares learning, mean square error methods, and stochastic approximation. Chapter 2 covers single agent reinforcement learning. Topics include learning value functions, Markov games, and TD learning with eligibility traces. Chapter 3 discusses two player games including two player matrix games with both pure and mixed strategies. Numerous algorithms and examples are presented. Chapter 4 cov
Who reads Multi-Agent Machine Learning : A Reinforcement Approach?
It is typically read by working professionals who need an authoritative practice reference.
Common subject areas: medicine, law, business, engineering.
- Author
- HOWARD M.SCHWARTZ, Howard M Schwartz, Schwartz, H. M., H. M. Schwartz
- Publisher
- Wiley & Sons, Incorporated, John
- Published
- 2014
- Language
- EN
- ISBN
- 9781322094762
- Category
- engineering
- Subjects
- Engineering, Mathematics, Science
- Updated
- 2026-03-25
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