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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| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Hoboken, New Jersey :
John Wiley & Sons, Inc
2014.
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| Edición: | 1st edition |
| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009629753206719 |
| Sumario: | "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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| Notas: | Description based upon print version of record. |
| Descripción Física: | 1 online resource (458 p.) |
| Bibliografía: | Includes bibliographical references at the end of each chapters and index. |
| ISBN: | 9781118884485 9781118884614 9781118884478 |
