A Concise Introduction to Multiagent Systems and Distributed Artificial Intelligence

Nikos Vlassis

ISBN 10: 3031004159 / ISBN 13: 9783031004155

Published by Springer International Publishing Dez 2007, 2007

About this Item

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

Bibliographic Details

Title: A Concise Introduction to Multiagent Systems...

Publisher: Springer International Publishing Dez 2007

Publication Date: 2007

Binding: Taschenbuch

Condition: Neu

About this title

Synopsis:

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.

About the Author:

Nikos Vlassis was born in 1970 in Corinth, Greece. He received an MSc (1993) and a PhD (1998) in Electrical and Computer Engineering from the National Technical University of Athens, Greece. In 1998 he joined the Informatics Institute of the University of Amsterdam, The Netherlands, as research fellow, and in 1999 he visited the Electrotechnical Laboratory (ETL, currently AIST) in Tsukuba, Japan, with a scholarship from the Japan Industrial Technology Association (MITI). From 2000 until 2006 he held an Assistant Professor position in the Informatics Institute of the University of Amsterdam, The Netherlands. Since 2007 he holds an Assistant Professor position in the Department of Production Engineering and Management of the Technical University of Crete, Greece. He is coauthor of about 100 papers on various topics in the fields of machine learning, multiagent systems, robotics, and computer vision, and has received numerous citations. Awards that he has received include the Dimitris Chorafas Foundation prize for young researchers in Engineering and Technology (Luzern, Switzerland, 1998), best-teacher mention at the University of Amsterdam (2001-2005), best scientific paper award with the paper "Using the max-plus algorithm for multiagent decision making in coordination graphs" in the annual RoboCup symposium (2005), and various distinctions with the UvA Trilearn robot soccer team including the 1st position at the RoboCup world championship (2003). His current research interests are in the areas of robotics, machine learning, and stochastic optimal control.