[robotics-worldwide] 2nd CFP: Workshop on Multiagent Sequential Decision Making Under Uncertainty (MSDM 2013)

Brenda Ng brenda.ng at gmail.com
Thu Jan 24 08:02:27 PST 2013


================================================================
                          CALL FOR PAPERS
                       The 8th Workshop on
 Multiagent Sequential Decision Making Under Uncertainty (MSDM)
                (to be held at AAMAS 2013)
=================================================================

May 6 or 7, 2013
St. Paul, Minnesota, USA
http://gaips.inesc-id.pt/~switwicki/msdm2013/

Dealing with uncertainty in complex dynamic environments is a basic
challenge to the operation of real-world robotic systems. Such a system
must be able to monitor the state of its components and environment in
order to form informed plans of intelligent action. In the case of a
multi-robot system (e.g., a team of collaborative rescue robots or
adversarial soccer-playing robots), each robotic agent needs to make
inferences about the other robotic agents as well, possibly under limited
communication or disinformation (in adversarial situations), over a course
of repeated interactions. Thus, multiagent sequential decision making under
uncertainty (MSDM) is a relevant topic for real-world application of
autonomous multi-robotic systems.

In sequential decision making, an agent (i.e., any autonomous entity -- a
robot, a human, or a software agent) seeks to choose the "best" 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.


Topics
----------------------------------------
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:

- Challenging conventional assumptions
 ... model specification: where do the models come from?
 ... what is an appropriate level of abstraction for decision making?
- Novel representations, algorithms and complexity results
- Comparisons of algorithms
- Relationships between models and their assumptions
- Decentralized vs. centralized planning approaches
- Online vs. offline planning
- Communication and coordination during execution
- Computational issues involving...
 ... large numbers of agents
 ... large numbers of states, observations and actions
 ... long decision horizons
- (Reinforcement) learning in partially observable multiagent systems
- Cooperative, competitive, and self-interested agents
- Application domains
- Benchmarks and evaluation methodologies
- Standardization of software
- High-level principles in MSDM: past trends and future directions


Important Dates
----------------------------------------
February 8, 2013     - Abstract submission due
February 12, 2013   - Paper submission due
March 8, 2013         - Notification of Acceptance
March 12, 2013       - Camera-ready submission due
May 6 or 7, 2013     - Day of Workshop


Submission Instructions
----------------------------------------
Authors are encouraged to submit papers up to 8 pages in length, as per the
instructions on the workshop homepage:
http://gaips.inesc-id.pt/~switwicki/msdm2013/
Each submission will be reviewed by at least three Program Committee
members. The review process will be "single-blind"; thus authors do not
have to remove their names when submitting papers.


Organizing Committee
----------------------------------------
Prashant Doshi  / University of Georgia
Jun-young Kwak / University of Southern California
Brenda Ng / Lawrence Livermore National Laboratory
Frans A. Oliehoek / Maastricht University
Stefan Witwicki / INESC-ID & Instituto Superior Técnico


Program Committee
----------------------------------------
Martin Allen / University of Wisconsin - La Crosse
Christopher Amato / MIT
Bikramjit Banerjee / University of Southern Mississippi
Raphen Becker / Google
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 Técnico & INESC-ID
Hala Mostafa / BBN Technologies
Abdel-Illah Mouaddib / Universit de Caen
Enrique Munoz de Cote / National Inst. of Astrophysics Optics and
Electronics
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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