103 citations · 124 across the 2 of their papers we have counts for
3 papers
cs.MA2020★ 103 cited
SMARTS: Scalable Multi-Agent Reinforcement Learning Training School for Autonomous Driving
Ming Zhou, Jun Luo, Julian Villella +34
Multi-agent interaction is a fundamental aspect of autonomous driving in the real world. Despite more than a decade of research and development, the problem of how to competently i…
cs.LG2020
Correcting Experience Replay for Multi-Agent Communication
Sanjeevan Ahilan, Peter Dayan
We consider the problem of learning to communicate using multi-agent reinforcement learning (MARL). A common approach is to learn off-policy, using data sampled from a replay buffe…
cs.MA2019★ 21 cited
Feudal Multi-Agent Hierarchies for Cooperative Reinforcement Learning
Sanjeevan Ahilan, Peter Dayan
We investigate how reinforcement learning agents can learn to cooperate. Drawing inspiration from human societies, in which successful coordination of many individuals is often fac…