10 citations · 18 across the 11 of their papers we have counts for
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cs.MA2025
Automata-Conditioned Cooperative Multi-Agent Reinforcement Learning
Beyazit Yalcinkaya, Marcell Vazquez-Chanlatte, Ameesh Shah +2
We study learning multi-task, multi-agent policies for cooperative, temporal objectives, under centralized training, decentralized execution. In this setting, using automata to rep…
cs.MA2025
Learning Symbolic Task Decompositions for Multi-Agent Teams
Ameesh Shah, Niklas Lauffer, Thomas Chen +2
One approach for improving sample efficiency in cooperative multi-agent learning is to decompose overall tasks into sub-tasks that can be assigned to individual agents. We study th…