Economically Founded Multiagent System
Tuomas Sandholm
Course Description
Multiagent systems research, a subfield of AI, studies the interactions
of computational agents. These agents can represent different real world
parties, and they can have different preference structures. Important
applications include manufacturing planning and scheduling among
multiple agile enterprises, markets for electricity, allocating and
pricing bandwidth in multi-provider multi- consumer computer networks,
network management, multiagent information gathering on the web,
distributed vehicle routing among independent dispatch centers,
electronic commerce, resource allocation in distributed operating
systems, meeting scheduling, scheduling of patient treatments across
hospitals, classroom scheduling, and planning and scheduling of multi-
contractor software projects, to name just a few. Multiagent systems can
save users' time, but they may also achieve better solutions (e.g. by
enhanced negotiation and coalition formation) than human agents can in
combinatorially and strategically complex domains.
A key research goal is to design open distributed systems in a
principled way that leads to globally desirable outcomes even though
every participating agent only considers its own good and may act
insincerely. The tutorial covers relevant results in AI, game theory,
market mechanisms, voting, auctions, coalition formation, and contract
nets. Emphasis is given to rigorous concepts, results, and algorithms -
both classic ones from microeconomics and recent ones from the
distributed AI community - that have direct applications to
computational multiagent systems. Implementation experiences will be
shared. Effects of different computational limitations (agents' bounded
rationality) are discussed as a key feature that has not received
adequate attention. Examples of real-world applications will be
presented.
The tutorial equips the serious systems builder with rigorous techniques
for making multiple self- interested agents cooperate efficiently. It
also serves to familiarize newcomers and executive level participants
with the issues involved. No prior knowledge is assumed in economics or
multiagent systems. A general familiarity with computer science will be
helpful.
About the Lecturers
Tuomas Sandholm
is assistant professor of computer science at Washington University. He
received the M.S. (B.S. included) with distinction in Industrial
Engineering and Management Science from the Helsinki University of
Technology, Finland, in 1991. From 1988 to 1992, he worked as a research
scientist in the software industry. He earned the M.S. and Ph.D. degrees
in computer science from the University of Massachusetts at Amherst in
1994 and 1996 respectively. He has published 23 refereed articles in AI
Journal, IJCAI, AAAI and other forums - as well as numerous book
chapters, technical reports and other papers. He has been a program
committee member for five major conferences, and a reviewer for seven
journals and numerous conferences. He has six years of experience
designing efficient multiagent systems. This work has focused both on
theory and implementations. He has also been involved in developing two
fielded AI systems: a pension law expert system and a large- scale
transportation optimization application.
higuchi@etl.go.jp
Last modified: Thu Feb 20 13:21:13 JST 1997