Multi-agent machine learning : a reinforcement approach / Howard M. Schwartz.

Includes bibliographical references and index.

'Multi-Agent Machine Learning: A Reinforcement Learning Approach is a framework to understanding different methods and approaches in multi-agent machine learning. It also provides cohesive coverage of the latest advances in multi-agent differential games and presents applications in game theory and robotics. Framework for understanding a variety of methods and approaches in multi-agent machine learning. Discusses methods of reinforcement learning such as a number of forms of multi-agent Q-learning Applicable to research professors and graduate students studying electrical and computer engineering, computer science, and mechanical and aerospace engineering'-- Provided by publisher.

'Provide an in-depth coverage of multi-player, differential games and Gam theory'-- Provided by publisher.