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

Ranjit Nair, Pradeep Varakantham, Milind Tambe, Makoto Yokoo

Research output: Contribution to journalConference article

12 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 a distributed policy generation algorithm that performs local search.

Original languageEnglish
Pages (from-to)1758-1760
Number of pages3
JournalIJCAI International Joint Conference on Artificial Intelligence
Publication statusPublished - Dec 1 2005
Event19th International Joint Conference on Artificial Intelligence, IJCAI 2005 - Edinburgh, United Kingdom
Duration: Jul 30 2005Aug 5 2005

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence

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