Call For Papers Workshop on Sequential Decision Making in Uncertain Multi-Agent Domains Held in conjunction with the Fifth International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS), Future University- Hakodate, 9th May, 2006 ------------------------------- Overview ------------------------------- Sequential decision making under uncertainty is the problem an agent faces when it tries to maximize its performance through interacting with its environment (and possibly other agents) based upon its observations of the world. Single-agent decision-theoretic approaches to this problem have centered around two primary models, the Markov Decision Problem (MDP) and the Partially Observable Markov Decision Problem (POMDP), depending on whether the agent's knowledge about the world is complete or partial. These mathematically rigorous models have been used very successfully in single-agent systems so it is only natural to apply them to systems with many agents. Just as in single-agent decision-theoretic work, the decision-theoretic multi-agent community has focused on two kinds of models: i) where each agent has complete knowledge about the state of the world, and ii) where each agent has partial (and potentially different) knowledge about the state of the world. The high computational complexity of finding optimal solutions in these multi-agent models has been a significant barrier. 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 to study the tradeoffs associated with the use of each. Furthermore, we will discuss the creation of online problem sets for testing the various algorithms to facilitate comparison. ------------------------------- Topics ------------------------------- The workshop will address a range of topics relating to new and existing models of multi-agent systems (i.e. MMDP, Dec-MDP, Dec-POMDP, Dec-MDP_Com, MTDP, COM-MTDP, R-MTDP, E-MTDP, EMT, I-POMDP, POSG, POIPSG, ND-POMDP, TI-Dec_MDP) including: - 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 - Theoretical and empirical results - Benchmarks and evaluation methodologies for comparing different approaches ------------------------------- Important Dates ------------------------------- Submission Deadline: February 1, 2006 Acceptance Notification: February 19, 2006 Camera-ready Copy: March 8, 2006 Workshop: May 9, 2006 ------------------------------- Submission Procedure ------------------------------- Authors are encouraged to submit papers up to 15 pages in length in the standard LaTeX Article format (12 pt font). Submissions should be sent to ranjit.nair@honeywell.com or raphen@cs.umass.edu in PostScript or PDF form. Each submission will be reviewed by at least two Program Committee members. ------------------------------- Organizing Committee ------------------------------- Ranjit Nair Knowledge Services Group, Honeywell Laboratories 3660 Technology Dr, #2703, Minneapolis MN 55418, USA Phone: +1(612) 951-7198 Fax: +1(612) 951 7438 ranjit.nair@honeywell.com http://teamcore.usc.edu/nair Raphen Becker Department of Computer Science, University of Massachusetts Amherst 140 Governor's Drive, Amherst, MA 01003, USA Phone: +1(413)545-1985 raphen@cs.umass.edu http://www.cs.umass.edu/~raphen ------------------------------- Program Committee ------------------------------- Daniel Bernstein University of Massachusetts Aurelie Beynier Université de Caen Dmitri Dolgov University of Michigan Prashant Doshi University of Georgia Ed Durfee University of Michigan Rosemary Emery-Montemerlo Carnegie Mellon University Alberto Finzi University of Roma Piotr Gmytrasiewicz University of Illinois Chicago Robert Goldman Smart Information Flow Technologies Claudia Goldman-Shenhar University of Haifa Eric Hansen Mississippi State University Victor Lesser University of Massachusetts Thomas Lukasiewicz University of Roma Abdel-Illah Mouaddib Université de Caen Praveen Paruchuri University of Southern California John Phelps Honeywell Laboratories David Pynadath Information Sciences Institute Zinovi Rabinovich Hebrew University Jeffrey Rosenschein Hebrew University Maayan Roth Carnegie Mellon University Jiaying Shen University of Massachusetts Milind Tambe University of Southern California Pradeep Varakantham University of Southern California Brian Williams Massachusetts Institute of Technology Ping Xuan Clark University Makoto Yokoo Kyushu University Shlomo Zilberstein University of Massachusetts