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 41–50 of 1718 papers

Title	Date	Tasks	Status	Hype	Score
A New Approach to Solving SMAC Task: Generating Decision Tree Code from Large Language Models	Oct 21, 2024	Decision MakingMulti-agent Reinforcement Learning	CodeCode Available	2	5
Maximum Entropy Heterogeneous-Agent Reinforcement Learning	Jun 19, 2023	MuJoCoMulti-agent Reinforcement Learning	CodeCode Available	2	5
ACE: Cooperative Multi-agent Q-learning with Bidirectional Action-Dependency	Nov 29, 2022	Decision MakingMulti-agent Reinforcement Learning	CodeCode Available	2	5
MOMAland: A Set of Benchmarks for Multi-Objective Multi-Agent Reinforcement Learning	Jul 23, 2024	BenchmarkingDecision Making	CodeCode Available	2	5
JaxMARL: Multi-Agent RL Environments and Algorithms in JAX	Nov 16, 2023	CPUGPU	CodeCode Available	2	5
A Cooperative-Competitive Multi-Agent Framework for Auto-bidding in Online Advertising	Jun 11, 2021	Multi-agent Reinforcement Learning	CodeCode Available	1	5
A Constrained Multi-Agent Reinforcement Learning Approach to Autonomous Traffic Signal Control	Mar 30, 2025	FairnessMulti-agent Reinforcement Learning	CodeCode Available	1	5
Cooperation and Fairness in Multi-Agent Reinforcement Learning	Oct 19, 2024	FairnessMulti-agent Reinforcement Learning	CodeCode Available	1	5
Attacking Cooperative Multi-Agent Reinforcement Learning by Adversarial Minority Influence	Feb 7, 2023	Continuous ControlMuJoCo	CodeCode Available	1	5
Asynchronous Multi-Agent Reinforcement Learning for Efficient Real-Time Multi-Robot Cooperative Exploration	Jan 9, 2023	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	1	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