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 1701–1710 of 1718 papers

Title	Date	Tasks	Status	Hype
A multi-agent reinforcement learning model of common-pool resource appropriation	Jul 20, 2017	Deep Reinforcement LearningMulti-agent Reinforcement Learning	CodeCode Available	1
Lenient Multi-Agent Deep Reinforcement Learning	Jul 14, 2017	Deep Reinforcement LearningMulti-agent Reinforcement Learning	CodeCode Available	1
Value-Decomposition Networks For Cooperative Multi-Agent Learning	Jun 16, 2017	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	1
ACCNet: Actor-Coordinator-Critic Net for "Learning-to-Communicate" with Deep Multi-agent Reinforcement Learning	Jun 10, 2017	Multi-agent Reinforcement Learningreinforcement-learning	—Unverified	0
Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments	Jun 7, 2017	Deep Reinforcement LearningMulti-agent Reinforcement Learning	CodeCode Available	1
Dynamic Safe Interruptibility for Decentralized Multi-Agent Reinforcement Learning	Apr 10, 2017	Multi-agent Reinforcement Learningreinforcement-learning	—Unverified	0
Deep Decentralized Multi-task Multi-Agent Reinforcement Learning under Partial Observability	Mar 17, 2017	Multi-agent Reinforcement Learningreinforcement-learning	—Unverified	0
Analysing Congestion Problems in Multi-agent Reinforcement Learning	Feb 28, 2017	Multi-agent Reinforcement Learningreinforcement-learning	—Unverified	0
Stabilising Experience Replay for Deep Multi-Agent Reinforcement Learning	Feb 28, 2017	Multi-agent Reinforcement LearningQ-Learning	CodeCode Available	1
Multi-agent Reinforcement Learning in Sequential Social Dilemmas	Feb 10, 2017	Multi-agent Reinforcement Learningreinforcement-learning	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