Automata-Conditioned Cooperative Multi-Agent Reinforcement Learning 事件

Automata-Conditioned Cooperative Multi-Agent Reinforcement Learning arXiv:2511.02304v2 Announce Type: replace-cross Abstract: We study learning multi-task, multi-agent policies for cooperative, temporal objectives, under centralized training, decentralized execution. In this setting, using automata to represent tasks assigned to agents enables breaking down a team-level objective into simpler, smaller sub-tasks. However, existing approaches remain sample-inefficient and are limited to the singl