Multi-Agent Machine Learning: A Reinforcement Approach

✍ Scribed by H. M. Schwartz

Publisher: Wiley
Year: 2014
Tongue: English
Leaves: 256
Edition: 1
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

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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