Concise Introduction to Multiagent Systems and Distributed Artificial Intelligence

Häftad, Engelska, 2007

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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.

Produktinformation

Utgivningsdatum2007-12-31
Mått191 x 235 x 6 mm
Vikt176 g
FormatHäftad
SpråkEngelska
SerieSynthesis Lectures on Artificial Intelligence and Machine Learning
Antal sidor71
FörlagSpringer International Publishing AG
ISBN9783031004155
OriginaltitelA Concise Introduction to Multiagent Systems and Distributed Artificial Intelligence

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Tillämpad matematik inom Naturvetenskap och teknik
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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.