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 491–500 of 1718 papers

Title	Date	Tasks	Status	Score
eQMARL: Entangled Quantum Multi-Agent Reinforcement Learning for Distributed Cooperation over Quantum Channels	May 24, 2024	Multi-agent Reinforcement Learning	CodeCode Available	5
Effects of Spectral Normalization in Multi-agent Reinforcement Learning	Dec 10, 2022	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	5
Multi-agent reinforcement learning for the control of three-dimensional Rayleigh-Bénard convection	Jul 31, 2024	Deep Reinforcement LearningMulti-agent Reinforcement Learning	CodeCode Available	5
Learning to Play General-Sum Games Against Multiple Boundedly Rational Agents	Jun 10, 2021	Decision MakingMulti-agent Reinforcement Learning	CodeCode Available	5
Expert-Free Online Transfer Learning in Multi-Agent Reinforcement Learning	Jan 26, 2025	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	5
A Generalist Hanabi Agent	Mar 17, 2025	Multi-agent Reinforcement Learning	CodeCode Available	5
CoMIX: A Multi-agent Reinforcement Learning Training Architecture for Efficient Decentralized Coordination and Independent Decision-Making	Aug 21, 2023	Decision MakingMulti-agent Reinforcement Learning	CodeCode Available	5
Towards Robust Multi-UAV Collaboration: MARL with Noise-Resilient Communication and Attention Mechanisms	Mar 4, 2025	counterfactualDecision Making	CodeCode Available	5
Enhancing Language Multi-Agent Learning with Multi-Agent Credit Re-Assignment for Interactive Environment Generalization	Feb 20, 2025	Multi-agent Reinforcement Learning	CodeCode Available	5
Aquarium: A Comprehensive Framework for Exploring Predator-Prey Dynamics through Multi-Agent Reinforcement Learning Algorithms	Jan 13, 2024	Multi-agent Reinforcement Learningreinforcement-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