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
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