Multi-Agent Machine Learning: A Reinforcement Approach

Multi-Agent Machine Learning: A Reinforcement Approach

作者: H. M. Schwartz
出版社: Wiley
出版在: 2014-08-11
ISBN-13: 9781118362082
ISBN-10: 111836208X
裝訂格式: Hardcover
總頁數: 256 頁





內容描述


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




相關書籍

Practical Artificial Intelligence with Swift: From Fundamental Theory to Development of Ai-Driven Apps

作者 Geldard Mars Manning Jonathon Buttfield-Addison Paris

2014-08-11

Data Mining: Next Generation Challenges and Future Directions (Paperback)

作者 Hillol Kargupta Anupam Joshi Krishnamoorthy Sivakumar Yelena Yesha

2014-08-11

Machine Learning: A Quantitative Approach (dhl)

作者 Henry H Liu

2014-08-11