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 51–60 of 1718 papers

Title	Date	Tasks	Status	Hype
Curriculum Learning With Counterfactual Group Relative Policy Advantage For Multi-Agent Reinforcement Learning	Jun 9, 2025	counterfactualMulti-agent Reinforcement Learning	CodeCode Available	1
Decentralized Social Navigation with Non-Cooperative Robots via Bi-Level Optimization	Jun 15, 2023	Collision AvoidanceMulti-agent Reinforcement Learning	CodeCode Available	1
Contrastive Identity-Aware Learning for Multi-Agent Value Decomposition	Nov 23, 2022	Contrastive LearningDiversity	CodeCode Available	1
Context-aware Communication for Multi-agent Reinforcement Learning	Dec 25, 2023	Multi-agent Reinforcement LearningQuantization	CodeCode Available	1
Cooperative Policy Learning with Pre-trained Heterogeneous Observation Representations	Dec 24, 2020	DecoderGraph Attention	CodeCode Available	1
Controlling Behavioral Diversity in Multi-Agent Reinforcement Learning	May 23, 2024	DiversityMulti-agent Reinforcement Learning	CodeCode Available	1
Counterfactual Conservative Q Learning for Offline Multi-agent Reinforcement Learning	Sep 22, 2023	counterfactualMulti-agent Reinforcement Learning	CodeCode Available	1
Cross Modality 3D Navigation Using Reinforcement Learning and Neural Style Transfer	Nov 5, 2021	Computed Tomography (CT)Diagnostic	CodeCode Available	1
A Constrained Multi-Agent Reinforcement Learning Approach to Autonomous Traffic Signal Control	Mar 30, 2025	FairnessMulti-agent Reinforcement Learning	CodeCode Available	1
Collaborative Visual Navigation	Jul 2, 2021	Multi-agent Reinforcement LearningNavigate	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