A Concise Introduction to Multiagent Systems and Distributed Artificial Intelligence (Synthesis Lectures on Artificial Intelligence and Machine Learning) - Softcover
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Multiagent systems is an expanding field that blends classical fields like game theory and decentralized control with modern fields like computer science and machine learning. Chapter 7 provides a short introduction to the rapidly expanding field of multiagent reinforcement learning.
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A Concise Introduction to Multiagent Systems and Distributed Artificial Intelligence (eng)
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A Concise Introduction to Multiagent Systems and Distributed Artificial Intelligence (Paperback or Softback)
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ISBN 13: 9783031004155
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A Concise Introduction to Multiagent Systems and Distributed Artificial Intelligence (Synthesis Lectures on Artificial Intelligence and Machine Learning)
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A Concise Introduction to Multiagent Systems and Distributed Artificial Intelligence (Synthesis Lectures on Artificial Intelligence and Machine Learning)
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A Concise Introduction to Multiagent Systems and Distributed Artificial Intelligence
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Springer International Publishing Dez 2007, 2007
ISBN 10: 3031004159
ISBN 13: 9783031004155
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Multiagent systems is an expanding field that blends classical fields like game theory and decentralized control with modern fields like computer science and machine learning. This monograph provides a concise introduction to the subject, covering the theoretical foundations as well as more recent developments in a coherent and readable manner. The text is centered on the concept of an agent as decision maker. Chapter 1 is a short introduction to the field of multiagent systems. Chapter 2 covers the basic theory of singleagent decision making under uncertainty. Chapter 3 is a brief introduction to game theory, explaining classical concepts like Nash equilibrium. Chapter 4 deals with the fundamental problem of coordinating a team of collaborative agents. Chapter 5 studies the problem of multiagent reasoning and decision making under partial observability. Chapter 6 focuses on the design of protocols that are stable against manipulations by self-interested agents. Chapter 7 provides a short introduction to the rapidly expanding field of multiagent reinforcement learning. The material can be used for teaching a half-semester course on multiagent systems covering, roughly, one chapter per lecture. 84 pp. Englisch. Seller Inventory # 9783031004155