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

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 1261–1270 of 1718 papers

Title	Date	Tasks	Status	Hype
Tesseract: Tensorised Actors for Multi-Agent Reinforcement Learning	May 31, 2021	Learning TheoryMulti-agent Reinforcement Learning	—Unverified	0
SHAQ: Incorporating Shapley Value Theory into Multi-Agent Q-Learning	May 31, 2021	FairnessMulti-agent Reinforcement Learning	CodeCode Available	1
MARL with General Utilities via Decentralized Shadow Reward Actor-Critic	May 29, 2021	Multi-agent Reinforcement Learning	—Unverified	0
KnowSR: Knowledge Sharing among Homogeneous Agents in Multi-agent Reinforcement Learning	May 25, 2021	Deep Reinforcement LearningKnowledge Distillation	—Unverified	0
From Motor Control to Team Play in Simulated Humanoid Football	May 25, 2021	Decision MakingImitation Learning	—Unverified	0
Searching Collaborative Agents for Multi-plane Localization in 3D Ultrasound	May 22, 2021	DiagnosticMulti-agent Reinforcement Learning	—Unverified	0
Cooperative Multi-Agent Reinforcement Learning with Sequential Credit Assignment	May 21, 2021	counterfactualMulti-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
Permutation Invariant Policy Optimization for Mean-Field Multi-Agent Reinforcement Learning: A Principled Approach	May 18, 2021	Inductive BiasMulti-agent Reinforcement Learning	—Unverified	0
Dependent Multi-Task Learning with Causal Intervention for Image Captioning	May 18, 2021	Image CaptioningMulti-agent Reinforcement Learning	—Unverified	0

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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