Publication Type

Conference Proceeding Article

Publication Date

9-2009

Abstract

Distributed POMDPs provide an expressive framework for modeling multiagent collaboration problems, but NEXPComplete complexity hinders their scalability and application in real-world domains. This paper introduces a subclass of distributed POMDPs, and TREMOR, an algorithm to solve such distributed POMDPs. The primary novelty of TREMOR is that agents plan individually with a single agent POMDP solver and use social model shaping to implicitly coordinate with other agents. Experiments demonstrate that TREMOR can provide solutions orders of magnitude faster than existing algorithms while achieving comparable, or even superior, solution quality.

Keywords

POMDP, Multiagent planning, Uncertainty, Partially observability

Discipline

Artificial Intelligence and Robotics | Business | Operations Research, Systems Engineering and Industrial Engineering

Research Areas

Intelligent Systems and Decision Analytics

Publication

Proceedings of the Nineteenth International Conference on Automated Planning and Scheduling: September 19-23, Thessaloniki, Greece

First Page

313

Last Page

320

Publisher

AAAI Press

City or Country

Menlo Park, CA

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

http://aaai.org/ocs/index.php/ICAPS/ICAPS09/paper/view/733