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.

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Papers

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Showing 1–10 of 1718 papers

Title	Date	Tasks	Status	Hype
Multi-Agent Reinforcement Learning for Autonomous Driving: A Survey	Aug 19, 2024	Autonomous DrivingDecision Making	CodeCode Available	5
SigmaRL: A Sample-Efficient and Generalizable Multi-Agent Reinforcement Learning Framework for Motion Planning	Aug 14, 2024	CPUMotion Planning	CodeCode Available	4
Unreal-MAP: Unreal-Engine-Based General Platform for Multi-Agent Reinforcement Learning	Mar 20, 2025	Multi-agent Reinforcement Learning	CodeCode Available	3
Dispelling the Mirage of Progress in Offline MARL through Standardised Baselines and Evaluation	Jun 13, 2024	Multi-agent Reinforcement Learning	CodeCode Available	3
MARLlib: A Scalable and Efficient Multi-agent Reinforcement Learning Library	Oct 11, 2022	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	3
On the Use and Misuse of Absorbing States in Multi-agent Reinforcement Learning	Nov 10, 2021	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	3
SPIRAL: Self-Play on Zero-Sum Games Incentivizes Reasoning via Multi-Agent Multi-Turn Reinforcement Learning	Jun 30, 2025	MathMulti-agent Reinforcement Learning	CodeCode Available	2
Multi-Agent Reinforcement Learning for Resources Allocation Optimization: A Survey	Apr 29, 2025	Decision MakingMulti-agent Reinforcement Learning	CodeCode Available	2
SocialJax: An Evaluation Suite for Multi-agent Reinforcement Learning in Sequential Social Dilemmas	Mar 18, 2025	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	2
ReMA: Learning to Meta-think for LLMs with Multi-Agent Reinforcement Learning	Mar 12, 2025	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	2

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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