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 401–410 of 1718 papers

Title	Date	Tasks	Status	Score
Interpretable Emergent Language Using Inter-Agent Transformers	May 4, 2025	Multi-agent Reinforcement Learning	CodeCode Available	5
Deep Multi-Agent Reinforcement Learning with Relevance Graphs	Nov 30, 2018	Deep Reinforcement LearningMulti-agent Reinforcement Learning	CodeCode Available	5
Smart Traffic Signals: Comparing MARL and Fixed-Time Strategies	May 20, 2025	Multi-agent Reinforcement Learning	CodeCode Available	5
Information State Embedding in Partially Observable Cooperative Multi-Agent Reinforcement Learning	Apr 2, 2020	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	5
Multi-Agent Reinforcement Learning with Focal Diversity Optimization	Feb 6, 2025	DiversityMulti-agent Reinforcement Learning	CodeCode Available	5
Learn How to Query from Unlabeled Data Streams in Federated Learning	Dec 11, 2024	BenchmarkingDecision Making	CodeCode Available	5
Learning to Solve the Min-Max Mixed-Shelves Picker-Routing Problem via Hierarchical and Parallel Decoding	Feb 14, 2025	Decision MakingMulti-agent Reinforcement Learning	CodeCode Available	5
Cooperative multi-agent reinforcement learning for high-dimensional nonequilibrium control	Nov 12, 2021	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	5
Communicating via Markov Decision Processes	Jul 17, 2021	Multi-agent Reinforcement Learning	CodeCode Available	5
Independent Learning in Constrained Markov Potential Games	Feb 27, 2024	Multi-agent Reinforcement Learning	CodeCode Available	5

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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