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Schwartz, H. M.

Multi-Agent Machine Learning: A Reinforcement Approach

Schwartz, H. M. - Multi-Agent Machine Learning: A Reinforcement Approach, ebook

109,35€

Ebook, ePUB with Adobe DRM
ISBN: 9781118884485
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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

Keywords: Intelligent Systems & Agents, Multi-Agent Machine Learnings, Mobile Robotics, Multi-Agent Systems, Game Theoretics, Single-Agent Reinforcement Learning, Multi-Agent Q-Learning, Learning Differential Games, Learning in Robotic Swarms

Author(s)
Publisher
John Wiley and Sons, Inc.
Publication year
2014
Language
en
Edition
1
Page amount
256 pages
Category
Technology, Energy, Traffic
Format
Ebook
eISBN (ePUB)
9781118884485
Printed ISBN
9781118362082

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