Decentralized and Lifelong-Adaptive Multi-Agent Collaborative Learning

arXiv:2403.06535v1 Announce Type: new
Abstract: Decentralized and lifelong-adaptive multi-agent collaborative learning aims to enhance collaboration among multiple agents without a central server, with each agent solving varied tasks over time. To achieve efficient collaboration, agents should: i) autonomously identify beneficial collaborative relationships in a decentralized manner; and ii) adapt to dynamically changing task observations. In this paper, we propose DeLAMA, a decentralized multi-agent lifelong collaborative learning algorithm with dynamic collaboration graphs. To promote autonomous collaboration relationship learning, we propose a …

agent arxiv collaborative cs.ai cs.lg cs.ma decentralized multi-agent type