In sequential decision making, an agent's objective is to choose actions, based on its observations of the world, in such a way that it expects to optimize its performance measure over the course of a series of such decisions. In environments where action consequences are non-deterministic or observations incomplete, Markov decision processes (MDPs) and partially observable MDPs (POMDPs) serve as the basis for principled approaches to single-agent sequential decision making. Extending these models to systems of multiple agents has become the subject of an increasingly active area of research over the past decade and a variety of models have emerged (e.g., MMDP, Dec-POMDP, MTDP, I-POMDP, and POSG). The high computational complexity of these models has driven researchers to develop multiagent planning and learning methods that exploit the structure present in agents' interactions, methods that provide efficient approximate solutions, and methods that distribute computation among the agents.
The MSDM workshop serves several purposes. The primary purpose is to bring together researchers in the field of MSDM to present and discuss new work and preliminary ideas. Moreover, we aim to identify recent trends, to establish important directions for future research, and to discuss some of the topics mentioned below such as challenging application areas (e.g., cooperative robotics, distributed sensor and/or communication networks, decision support systems) and suitable evaluation methodologies. Lastly, MSDM seeks to bring researchers from other AAMAS communities together in order to facilitate consensus among different models and methods, thus making the field more accessible to new researchers and practitioners.
Multiagent sequential decision making comprises (1) problem representation, (2) planning, (3) coordination, and (4) learning. The MSDM workshop addresses this full range of aspects. Topics of particular interest include:
Dr. Kobi Gal (Ben-Gurion University)
This year, we are excited to be hosting a joint panel of the MSDM and ALA worshops. We have confirmed the participation of Shlomo Zilberstein, Peter Stone, Milind Tambe, and Sandip Sen.
Planning under Uncertainty for Coordinating Infrastructural Maintenance
Joris Scharpff, Matthijs T.J. Spaan, Leentje Volker and Mathijs de Weerdt
Asynchronous Execution in Multiagent POMDPs: Reasoning over Partially-Observable Events
João V. Messias, Matthijs T.J. Spaan and Pedro U. Lima
Organizational Design Principles and Techniques for Decision-Theoretic Agents
Jason Sleight and Edmund H. Durfee
Rehearsal Based Multi-agent Reinforcement Learning of Decentralized Plans
Landon Kraemer and Bikramjit Banerjee
Counterfactual Regret Minimization for Decentralized Planning
Bikramjit Banerjee and Landon Kraemer
Automated Generation of Interaction Graphs for Value-Factored Decentralized POMDPs
William Yeoh, Akshat Kumar and Shlomo Zilberstein
Opponent modeling and planning against non-stationary strategies
Pablo Hernandez-Leal, Enrique Muñoz de Cote and L. Enrique Sucar
Qualitative Planning under Partial Observability in Multi-Agent Domains
Ronen I. Brafman, Guy Shani and Shlomo Zilberstein
Solving Dec-POMDPs by Genetic Algorithms: Robot Soccer Case Study
Okan Aşik and H. Levent Akin
A Coordinated MDP Approach to Multi-Agent Planning for Resource Allocation, with Applications to Healthcare
Hadi Hosseini, Jesse Hoey and Robin Cohen
Bayesian Reinforcement Learning for Multiagent Systems with State Uncertainty
Christopher Amato and Frans A. Oliehoek
Prashant Doshi | University of Georgia |
Stefan Witwicki | INESC-ID, Instituto Superior Técnico |
Jun-young Kwak | University of Southern California |
Frans A. Oliehoek | Maastricht University |
Brenda Ng | Lawrence Livermore National Laboratory |
Martin Allen | University of Wisconsin - La Crosse |
Christopher Amato | MIT |
Bikramjit Banerjee | University of Southern Mississippi |
Raphen Becker | |
Daniel Bernstein | Fiksu, Inc. |
Aurélie Beynier | University Pierre and Marie Curie (Paris 6) |
Alan Carlin | University of Massachusetts |
Georgios Chalkiadakis | Technical University of Crete |
François Charpillet | INRIA-Loria |
Ed Durfee | University of Michigan |
Alberto Finzi | Università di Napoli |
Piotr Gmytrasiewicz | University of Illinois Chicago |
Claudia Goldman | GM Advanced Technical Center Israel |
Akshat Kumar | IBM Research, India |
Michail Lagoudakis | Technical University of Crete |
Francisco Melo | Instituto Superior Tecnico/INESC-ID |
Hala Mostafa | BN Technologies |
Abdel-Illah Mouaddib | universit de Caen |
Enrique Munoz de Cote | INAOE, Mexico |
Simon Parsons | City University of New York |
Praveen Paruchuri | Carnegie Mellon University |
David Pynadath | Institute for Creative Technologies, USC |
Zinovi Rabinovich | Mobileye |
Anita Raja | University of North Carolina at Charlotte |
Paul Scerri | Carnegie Mellon University |
Jiaying Shen | Nuance Communications |
Matthijs Spaan | Delft University of Technology |
Peter Stone | University of Texas at Austin |
Karl Tuyls | Maastricht University |
Jianhui Wu | Amazon |
Ping Xuan | Hewlett-Packard |
Makoto Yokoo | Kyushu University |
Chongjie Zhang | University of Massachusetts |
Shlomo Zilberstein | University of Massachusetts |
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This workshop is supported, in part, by the Portuguese Fundação para a Ciéncia e Tecnologia (FCT) and by Carnegie Mellon Portugal Program and its Information and Communications Technologies Institute, under project CMU-PT/SIA/0023/2009 ("MAIS-S"), and by the FCT (INESC-ID multiannual funding) under project PEst-OE/EEI/LA0021/2011. |