103 citations · 127 across the 4 of their papers we have counts for
4 papers
A Succinct Summary of Reinforcement Learning
Sanjeevan Ahilan
This document is a concise summary of many key results in single-agent reinforcement learning (RL). The intended audience are those who already have some familiarity with RL and ar…
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…
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…
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…