Multi-agent machine learning a reinforcement approach
"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...
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| Format: | UnknownFormat |
| Sprache: | eng |
| Veröffentlicht: |
Hoboken, NJ
Wiley
2014
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| Online Zugang: | Cover Inhaltsverzeichnis Cover Inhaltstext |
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| Zusammenfassung: | "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"-- "Provide an in-depth coverage of multi-player, differential games and Gam theory"-- |
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| Beschreibung: | Literaturangaben |
| Beschreibung: | XI, 242 S. Ill., graph. Darst. |
| ISBN: | 9781118362082 978-1-118-36208-2 |