Vlassis, Nikos.
A Concise Introduction to Multiagent Systems and Distributed Artificial Intelligence [electronic resource] / by Nikos Vlassis. - 1st ed. 2007. - XII, 71 p. online resource. - Synthesis Lectures on Artificial Intelligence and Machine Learning, 1939-4616 . - Synthesis Lectures on Artificial Intelligence and Machine Learning, .
Introduction -- Rational Agents -- Strategic Games -- Coordination -- Partial Observability -- Mechanism Design -- Learning.
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.
9783031015434
10.1007/978-3-031-01543-4 doi
Artificial intelligence.
Machine learning.
Neural networks (Computer science) .
Artificial Intelligence.
Machine Learning.
Mathematical Models of Cognitive Processes and Neural Networks.
Q334-342 TA347.A78
006.3
A Concise Introduction to Multiagent Systems and Distributed Artificial Intelligence [electronic resource] / by Nikos Vlassis. - 1st ed. 2007. - XII, 71 p. online resource. - Synthesis Lectures on Artificial Intelligence and Machine Learning, 1939-4616 . - Synthesis Lectures on Artificial Intelligence and Machine Learning, .
Introduction -- Rational Agents -- Strategic Games -- Coordination -- Partial Observability -- Mechanism Design -- Learning.
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.
9783031015434
10.1007/978-3-031-01543-4 doi
Artificial intelligence.
Machine learning.
Neural networks (Computer science) .
Artificial Intelligence.
Machine Learning.
Mathematical Models of Cognitive Processes and Neural Networks.
Q334-342 TA347.A78
006.3