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CALL FOR PAPERS
AAMAS 2010 Workshop
Multi-agent Sequential Decision-Making in Uncertain Domains
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Fifth Workshop in the MSDM series
May 10 or 11, 2010
Toronto, Canada
http://rbrserver.cs.umass.edu/~camato/msdm2010/msdm2010.htm
Sequential decision making under uncertainty is the problem an agent
faces when it seeks to maximize its performance in an environment
while making action choices based upon its observations of the
world. Decision-theoretic approaches have been used very successfully
in single-agent systems, so it is only natural to apply them to
systems with many agents. The high computational complexity of finding
optimal solutions in these multi-agent models has been a significant
barrier to applying them to complex real world problems. Much of the
work in this area relates to addressing this complexity through
exploiting problem structure like locality of interaction,
decomposition of reward and independence between the agents, and
through approximate algorithms that converge to a local optimum
instead of a global optimum.
The purpose of this workshop is to bring together researchers in the
field of sequential decision-making in stochastic multi-agent systems
to present and discuss promising new work, to discuss the
relationships between the various models in use, and to establish
important directions and goals for further research and
collaboration. This workshop will strive to develop consensus within
the community on benchmarks and evaluation methodology in order to
contrast the alternative approaches and models, and also to study the
associated trade-offs. Furthermore, we will discuss the creation of
online problem sets for testing the various algorithms to facilitate
comparison.
Possible topics include:
- Relationships between the models and their assumptions
- Algorithms for policy generation and coordination
- Comparisons of algorithms
- Distributed vs. centralized planning
- Online vs. offline planning
- Communication during policy generation
- Communication decisions during execution
- Techniques for scaling problems
- Identifying subclasses of problems and their complexity
- Cooperative and competitive agent systems
- Partially Observable Stochastic Games and related game-theoretic
frameworks
- Theoretical and empirical results
- Benchmarks and evaluation methodologies for comparing different approaches
Important Dates
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February 2, 2010 - Submission deadline (strict)
March 2, 2010 - Notification of Acceptance
May 10 or 11, 2010 - Workshop
Submission instructions
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Authors are encouraged to submit papers up to 8 pages in length in the
AAMAS2010 format. Submissions should be uploaded in PDF form
at http://www.easychair.org/conferences/?conf=msdm2010 . Each
submission will be reviewed by at least two Program Committee members.
Organizing Committee
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Matthijs Spaan, Institute for Systems and Robotics, Instituto Superior
Técnico
Christopher Amato, Computer Science Department, University of
Massachusetts at Amherst
Georgios Chalkiadakis, School of Electronics and Computer Science,
University of Southampton
Prashant Doshi, Department of Computer Science, University of Georgia
Abdel-Illah Mouaddib, Lab. of GREYC-CNRS, University of Caen Basse-Normandie
Program Committee
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Martin Allen, Connecticut College
Aurelie Beynier, University Pierre and Marie Curie (Paris 6)
Brahim Chaib-draa, Laval University
François Charpillet, LORIA
Ed Durfee, University of Michigan
Alessandro Farinelli, University of Verona
Robert Goldman, Smart Information Flow Technologies
Piotr Gmytrasiewicz, University of Illinois Chicago
Eric Hansen, Mississippi State University
Sven Koenig, University of Southern California
Michail Lagoudakis, Technical University of Crete
Francisco Melo, INESC-ID Lisboa
Enrique Munoz de Cote, University of Southampton
Frans Oliehoek, University of Amsterdam
Simon Parsons, Brooklyn College
Pascal Poupart, University of Waterloo
David Pynadath, Information Sciences Institute
Xia Qu, University of Georgia
Zinovi Rabinovich, University of Southampton
W.T. Luke Teacy, University of Ulster
Karl Tuyls, Maastricht University
Pradeep Varakantham, Singapore Management University
Makoto Yokoo, Kyushu University
Shlomo Zilberstein, University of Massachusetts
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