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Synopsis
Multiagent systems is an expanding field that blends clical 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 clical 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.
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- ISBN 10 3031004159
- ISBN 13 9783031004155
- BindingPaperback
- LanguageEnglish
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A Concise Introduction to Multiagent Systems and Distributed Artificial Intelligence
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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
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A Concise Introduction to Multiagent Systems and Distributed Artificial Intelligence
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ISBN 10: 3031004159
ISBN 13: 9783031004155
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. Seller Inventory # 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
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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 theor. Seller Inventory # 608128844
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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 Nature Switzerland, Springer International Publishing Dez 2007, 2007
ISBN 10: 3031004159
ISBN 13: 9783031004155
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Taschenbuch. Condition: Neu. 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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 84 pp. Englisch. Seller Inventory # 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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