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 441–450 of 1718 papers

Title	Date	Tasks	Status	Score
GOV-REK: Governed Reward Engineering Kernels for Designing Robust Multi-Agent Reinforcement Learning Systems	Apr 1, 2024	Multi-agent Reinforcement Learning	CodeCode Available	5
Context-Aware Bayesian Network Actor-Critic Methods for Cooperative Multi-Agent Reinforcement Learning	Jun 2, 2023	Multi-agent Reinforcement Learning	CodeCode Available	5
GHQ: Grouped Hybrid Q Learning for Heterogeneous Cooperative Multi-agent Reinforcement Learning	Mar 2, 2023	Multi-agent Reinforcement LearningQ-Learning	CodeCode Available	5
Generalising Multi-Agent Cooperation through Task-Agnostic Communication	Mar 11, 2024	Multi-agent Reinforcement Learning	CodeCode Available	5
Conservative and Risk-Aware Offline Multi-Agent Reinforcement Learning	Feb 13, 2024	Multi-agent Reinforcement LearningQ-Learning	CodeCode Available	5
Generalizable Agent Modeling for Agent Collaboration-Competition Adaptation with Multi-Retrieval and Dynamic Generation	Jun 20, 2025	Multi-agent Reinforcement LearningSMAC	CodeCode Available	5
Gifting in multi-agent reinforcement learning	May 5, 2020	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	5
HAMMER: Multi-Level Coordination of Reinforcement Learning Agents via Learned Messaging	Jan 18, 2021	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	5
Homogeneous Learning: Self-Attention Decentralized Deep Learning	Oct 11, 2021	Deep LearningFederated Learning	CodeCode Available	5
Finding Friend and Foe in Multi-Agent Games	Jun 5, 2019	counterfactualMulti-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