Networked Distributed POMDPs: A Synthesis of Distributed Constraint Optimization and POMDPs
Conference Proceeding Article
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.
Artificial Intelligence and Robotics | Business | Operations Research, Systems Engineering and Industrial Engineering
Intelligent Systems and Decision Analytics
Proceedings of the Twentieth National Conference on Artificial Intelligence, AAAI
NAIR, Ranjit; VARAKANTHAM, Pradeep Reddy; Tambe, Milind; and Yokoo, Makoto.
Networked Distributed POMDPs: A Synthesis of Distributed Constraint Optimization and POMDPs. (2005). Proceedings of the Twentieth National Conference on Artificial Intelligence, AAAI. 133-139. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/955