Buch, Englisch, 71 Seiten, Paperback, Format (B × H): 187 mm x 235 mm
Reihe: Synthesis Lectures on Artificial Intelligence and Machine Learning
Buch, Englisch, 71 Seiten, Paperback, Format (B × H): 187 mm x 235 mm
Reihe: Synthesis Lectures on Artificial Intelligence and Machine Learning
ISBN: 978-1-59829-526-9
Verlag: Morgan & Claypool Publishers
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.
A Concise Introduction to Multiagent Systems and Distributed Artificial Intelligence jetzt bestellen!
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.
Autoren/Hrsg.
Weitere Infos & Material
- Introduction
- Rational Agents
- Strategic Games
- Coordination
- Partial Observability
- Mechanism Design
- Learning
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