载入...
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...
| 主要作者: | |
|---|---|
| 格式: | Printed Book |
| 语言: | English |
| 出版: |
New Jersey:
Wiley,
2014.
|
| 主题: | |
| 在线阅读: | http://catalogimages.wiley.com/images/db/jimages/9781118362082.jpg |
| 总结: | "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"-- |
|---|---|
| 实物描述: | xi, 242 pages : |
| ISBN: | 9781118362082 (hardback) 111836208X (hardback) |