Multi‐Agent Machine Learning: A Reinforcement Approach by Howard M. SchwartzEnglish | PDF | 2014 | 251 Pages | ISBN : 111836208X | 2.57 MB
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.