Cover image for Multi-agent machine learning : a reinforcement approach
Title:
Multi-agent machine learning : a reinforcement approach
Author:
Schwartz, Howard M., author.
ISBN:
9781118884614

9781118884478

9781322094762
Physical Description:
1 online resource (xi, 242 pages)
Abstract:
"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.
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E-Book 341941-1001 ONLINE(341941.1)
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