Multi-Agent Decentralized Belief Propagation on Graphs
Abstract
We consider the problem of interactive partially observable Markov decision processes (I-POMDPs), where the agents are located at the nodes of a communication network. Specifically, we assume a certain message type for all messages. Moreover, each agent makes individual decisions based on the interactive belief states, the information observed locally and the messages received from its neighbors over the network. Within this setting, the collective goal of the agents is to maximize the globally averaged return over the network through exchanging information with their neighbors. We propose a decentralized belief propagation algorithm for the problem, and prove the convergence of our algorithm. Finally we show multiple applications of our framework. Our work appears to be the first study of decentralized belief propagation algorithm for networked multi-agent I-POMDPs.
- Publication:
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arXiv e-prints
- Pub Date:
- November 2020
- DOI:
- 10.48550/arXiv.2011.04501
- arXiv:
- arXiv:2011.04501
- Bibcode:
- 2020arXiv201104501C
- Keywords:
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- Computer Science - Artificial Intelligence;
- Computer Science - Machine Learning
- E-Print:
- 16 pages. arXiv admin note: text overlap with arXiv:1109.2135, arXiv:1209.1695, arXiv:1802.08757 by other authors