Networked distributed POMDPs: A synthesis of distributed constraint optimization and POMDPs

Ranjit Nair, Pradeep Varakantham, Milind Tambe, Makoto Yokoo

Research output: Contribution to conferencePaper

106 Citations (Scopus)

Abstract

In many real-world multiagent applications such as distributed sensor nets, a network of agents is formed based on each agent's limited interactions with a small number of neighbors. While distributed POMDPs capture the real-world uncertainty in multiagent domains, they fail to exploit such locality of interaction. Distributed constraint optimization (DCOP) captures the locality of interaction but fails to capture planning under uncertainty. This paper present a new model synthesized from distributed POMDPs and DCOPs, called Networked Distributed POMDPs (ND-POMDPs). Exploiting network structure enables us to present two novel algorithms for ND-POMDPs: a distributed policy generation algorithm that performs local search and a systematic policy search that is guaranteed to reach the global optimal.

Original languageEnglish
Pages133-139
Number of pages7
Publication statusPublished - Dec 1 2005
Event20th National Conference on Artificial Intelligence and the 17th Innovative Applications of Artificial Intelligence Conference, AAAI-05/IAAI-05 - Pittsburgh, PA, United States
Duration: Jul 9 2005Jul 13 2005

Other

Other20th National Conference on Artificial Intelligence and the 17th Innovative Applications of Artificial Intelligence Conference, AAAI-05/IAAI-05
CountryUnited States
CityPittsburgh, PA
Period7/9/057/13/05

All Science Journal Classification (ASJC) codes

  • Software
  • Artificial Intelligence

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    Nair, R., Varakantham, P., Tambe, M., & Yokoo, M. (2005). Networked distributed POMDPs: A synthesis of distributed constraint optimization and POMDPs. 133-139. Paper presented at 20th National Conference on Artificial Intelligence and the 17th Innovative Applications of Artificial Intelligence Conference, AAAI-05/IAAI-05, Pittsburgh, PA, United States.