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 411–420 of 1718 papers

Title	Date	Tasks	Status	Score
Independent Learning in Constrained Markov Potential Games	Feb 27, 2024	Multi-agent Reinforcement Learning	CodeCode Available	5
Inferring Latent Temporal Sparse Coordination Graph for Multi-Agent Reinforcement Learning	Mar 28, 2024	Graph LearningMulti-agent Reinforcement Learning	CodeCode Available	5
Communicating via Markov Decision Processes	Jul 17, 2021	Multi-agent Reinforcement Learning	CodeCode Available	5
Classifying Ambiguous Identities in Hidden-Role Stochastic Games with Multi-Agent Reinforcement Learning	Oct 24, 2022	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	5
Reinforcement Learning from Hierarchical Critics	Feb 8, 2019	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	5
Cooperative Artificial Intelligence	Feb 20, 2022	Multi-agent Reinforcement LearningNavigate	CodeCode Available	5
A Structured Prediction Approach for Generalization in Cooperative Multi-Agent Reinforcement Learning	Oct 19, 2019	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	5
Hierarchical Cooperative Multi-Agent Reinforcement Learning with Skill Discovery	Dec 7, 2019	Multi-agent Reinforcement LearningQ-Learning	CodeCode Available	5
Homogeneous Learning: Self-Attention Decentralized Deep Learning	Oct 11, 2021	Deep LearningFederated Learning	CodeCode Available	5
Cooperative and Asynchronous Transformer-based Mission Planning for Heterogeneous Teams of Mobile Robots	Oct 8, 2024	Decision MakingMulti-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