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...
Cote: | Libro Electrónico |
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Autres auteurs: | |
Format: | Électronique eBook |
Langue: | Inglés |
Publié: |
Hoboken, NJ :
John Wiley & Sons,
[2014]
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Sujets: | |
Accès en ligne: | Texto completo Texto completo |
Résumé: | "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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Description matérielle: | 1 online resource |
Bibliographie: | Includes bibliographical references and index. |
ISBN: | 9781118884485 1118884485 9781118884478 1118884477 9781118884614 1118884612 9781322094762 1322094764 |