Collaborative Information Dissemination with Graph-based Multi-Agent Reinforcement Learning

arXiv:2308.16198v3 Announce Type: replace
Abstract: Efficient information dissemination is crucial for supporting critical operations across domains like disaster response, autonomous vehicles, and sensor networks. This paper introduces a Multi-Agent Reinforcement Learning (MARL) approach as a significant step forward in achieving more decentralized, efficient, and collaborative information dissemination. We propose a Partially Observable Stochastic Game (POSG) formulation for information dissemination empowering each agent to decide on message forwarding independently, based on the observation of their one-hop neighborhood. This constitutes a significant …

abstract agent arxiv autonomous autonomous vehicles collaborative cs.ai cs.lg cs.ma cs.ni decentralized disaster disaster response domains graph graph-based information multi-agent networks observable operations paper reinforcement reinforcement learning sensor type vehicles