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

Ranjit Nair, Pradeep Varakantham, Milind Tambe, Makoto Yokoo

研究成果: ジャーナルへの寄稿Conference article

11 引用 (Scopus)


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.

ジャーナルIJCAI International Joint Conference on Artificial Intelligence
出版物ステータス出版済み - 12 1 2005
イベント19th International Joint Conference on Artificial Intelligence, IJCAI 2005 - Edinburgh, 英国
継続期間: 7 30 20058 5 2005


All Science Journal Classification (ASJC) codes

  • Artificial Intelligence