Screen LibraryMulti-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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| Main Authors: | |
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| Published: |
Wiley,
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| Publisher Address: | Hoboken, New Jersey : |
| Publication Dates: | [2014] |
| Literature type: | Book |
| Language: | English |
| Subjects: | |
| Summary: |
"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 engine "Provide an in-depth coverage of multi-player, differential games and Gam theory"-- |
| Carrier Form: | xi, 242 pages ; 25 cm |
| Bibliography: | Includes bibliographical references and index. |
| ISBN: |
9781118362082 (hardback) : 111836208X (hardback) |
| Index Number: | Q325 |
| CLC: |
TP181 O225 |
| Call Number: | O225/S399 |