Matthew E. Taylor's Publications

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Exploiting Coordination Locales in Distributed POMDPs via Social Model Shaping

Pradeep Varakantham, Jun-young Kwak, Matthew E. Taylor, Janusz Marecki, Paul Scerri, and Milind Tambe. Exploiting Coordination Locales in Distributed POMDPs via Social Model Shaping. In Proceedings of the Nineteenth International Conference on Automated Planning and Scheduling (ICAPS), September 2009.
ICAPS-2009

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Abstract

Distributed POMDPs provide an expressive framework for modeling multiagent collaboration problems, but NEXP-Complete 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.

BibTeX Entry

@inproceedings(ICAPS09-Varakantham,
  author="Pradeep Varakantham and Jun-young Kwak and Matthew E.\ Taylor and
  Janusz Marecki and Paul Scerri and Milind Tambe",
  title="Exploiting Coordination Locales in Distributed {POMDP}s via Social
  Model Shaping",
  Booktitle="Proceedings of the Nineteenth International Conference on
  Automated Planning and Scheduling ({ICAPS})",
  month="September",
  year= "2009",
  wwwnote={<a href="http://icaps09.uom.gr">ICAPS-2009</a>},
  abstract={ Distributed POMDPs provide an expressive framework for
   modeling multiagent collaboration problems, but NEXP-Complete
   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.},
)

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