Multi-Agent Machine Learning: A Reinforcement Approach

H. M. Schwartz

Multi-Agent Machine Learning: A Reinforcement Approach

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商品描述

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

商品描述(中文翻譯)

《多智能體機器學習：一種強化學習方法》是一個理解多智能體機器學習不同方法和途徑的框架。它還提供了對多智能體微分博弈的最新進展的全面覆蓋，並介紹了在博弈論和機器人領域的應用。

• 理解多智能體機器學習的各種方法和途徑的框架。
• 討論了強化學習的方法，如多智能體Q學習的多種形式。
• 適用於研究電機與電腦工程、計算機科學以及機械與航空航天工程的研究教授和研究生。

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