@conference {1509591,
	title = {Networked Distributed POMDPs: A Synthesis of Distributed Constraint Optimization and POMDPs},
	booktitle = {Twentieth AAAI-05 National Conference on Artificial Intelligence},
	year = {2005},
	abstract = {In many real-world multiagent applications such as distributed sensor nets, a network of agents is formed based
on each agent{\textquoteright}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.},
	author = {Ranjit Nair and Varakantham, Pradeep and Tambe, Milind and Makoto Yokoo}
}
