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 181–190 of 1718 papers

Title	Date	Tasks	Status	Hype
Laser Learning Environment: A new environment for coordination-critical multi-agent tasks	Apr 4, 2024	Multi-agent Reinforcement LearningQ-Learning	CodeCode Available	1
Learning a Decentralized Multi-arm Motion Planner	Nov 5, 2020	Motion PlanningMulti-agent Reinforcement Learning	CodeCode Available	1
ACE-HGNN: Adaptive Curvature Exploration Hyperbolic Graph Neural Network	Oct 15, 2021	Graph LearningGraph Neural Network	CodeCode Available	1
Learning Multi-Agent Communication through Structured Attentive Reasoning	Dec 1, 2020	Decision MakingDeep Reinforcement Learning	CodeCode Available	1
Collaborative Visual Navigation	Jul 2, 2021	Multi-agent Reinforcement LearningNavigate	CodeCode Available	1
Learning to Cooperate with Humans using Generative Agents	Nov 21, 2024	Multi-agent Reinforcement Learning	CodeCode Available	1
Coach-Player Multi-Agent Reinforcement Learning for Dynamic Team Composition	May 18, 2021	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	1
Battlesnake Challenge: A Multi-agent Reinforcement Learning Playground with Human-in-the-loop	Jul 20, 2020	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	1
Bayesian Action Decoder for Deep Multi-Agent Reinforcement Learning	Nov 4, 2018	DecoderMulti-agent Reinforcement Learning	CodeCode Available	1
CityLearn: Standardizing Research in Multi-Agent Reinforcement Learning for Demand Response and Urban Energy Management	Dec 18, 2020	energy managementManagement	CodeCode Available	1

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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