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...
| Άλλοι συγγραφείς: | |
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| Μορφή: | Ηλ. βιβλίο |
| Γλώσσα: | English |
| Έκδοση: |
Hoboken, NJ :
John Wiley & Sons,
[2014]
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| Θέματα: | |
| Διαθέσιμο Online: | Full Text via HEAL-Link |
| Περίληψη: | "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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| Φυσική περιγραφή: | 1 online resource. |
| Βιβλιογραφία: | Includes bibliographical references and index. |
| ISBN: | 9781118884485 (ePub) 1118884485 (ePub) 9781118884478 (Adobe PDF) 1118884477 (Adobe PDF) 9781118884614 1118884612 9781322094762 1322094764 |
| DOI: | 10.1002/9781118884614 |
