Multi-agent Reinforcement Learning

The target of Multi-agent Reinforcement Learning is to solve complex problems by integrating multiple agents that focus on different sub-tasks. In general, there are two types of multi-agent systems: independent and cooperative systems.

Source: Show, Describe and Conclude: On Exploiting the Structure Information of Chest X-Ray Reports

Papers

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Showing 41–50 of 1718 papers

Title	Date	Tasks	Status	Hype
Learning to Fly -- a Gym Environment with PyBullet Physics for Reinforcement Learning of Multi-agent Quadcopter Control	Mar 3, 2021	BenchmarkingMulti-agent Reinforcement Learning	CodeCode Available	2
Emergent Reciprocity and Team Formation from Randomized Uncertain Social Preferences	Nov 10, 2020	Multi-agent Reinforcement Learning	CodeCode Available	2
SMARTS: Scalable Multi-Agent Reinforcement Learning Training School for Autonomous Driving	Oct 19, 2020	Autonomous DrivingMulti-agent Reinforcement Learning	CodeCode Available	2
PettingZoo: Gym for Multi-Agent Reinforcement Learning	Sep 30, 2020	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	2
Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning	Mar 19, 2020	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	2
The Decrypto Benchmark for Multi-Agent Reasoning and Theory of Mind	Jun 25, 2025	Multi-agent Reinforcement LearningNavigate	CodeCode Available	1
Chasing Moving Targets with Online Self-Play Reinforcement Learning for Safer Language Models	Jun 9, 2025	Multi-agent Reinforcement LearningSafety Alignment	CodeCode Available	1
Curriculum Learning With Counterfactual Group Relative Policy Advantage For Multi-Agent Reinforcement Learning	Jun 9, 2025	counterfactualMulti-agent Reinforcement Learning	CodeCode Available	1
Sorrel: A simple and flexible framework for multi-agent reinforcement learning	May 30, 2025	Multi-agent Reinforcement LearningPhilosophy	CodeCode Available	1
JaxRobotarium: Training and Deploying Multi-Robot Policies in 10 Minutes	May 10, 2025	BenchmarkingGPU	CodeCode Available	1

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All datasets ParticleEnvs Cooperative Communication SMAC-Exp UAV Logistics

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	MATD3	final agent reward	-14	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DRIMA	Median Win Rate	15	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Fusion-Multi-Actor-Attention-Critic	Average Reward	39	—	Unverified