Multi-Agent Machine Learning: A Reinforcement Approach
暫譯: 多代理機器學習：強化學習方法

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)

多代理機器學習：強化學習方法是一個理解多代理機器學習中不同方法和途徑的框架。它還提供了對多代理微分遊戲最新進展的全面覆蓋，並展示了在博弈論和機器人技術中的應用。

• 理解多代理機器學習中各種方法和途徑的框架。
• 討論強化學習的方法，例如多代理 Q-learning 的多種形式。
• 適用於研究教授和研究電機與計算機工程、計算機科學以及機械與航空航天工程的研究生。

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