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 221–230 of 1718 papers

Title	Date	Tasks	Status	Hype
Multi-Agent Trust Region Learning	Jan 1, 2021	Atari GamesMuJoCo	CodeCode Available	1
Multi-Agent Reinforcement Learning for Unmanned Aerial Vehicle Coordination by Multi-Critic Policy Gradient Optimization	Dec 31, 2020	Collision AvoidanceManagement	CodeCode Available	1
Cooperative Policy Learning with Pre-trained Heterogeneous Observation Representations	Dec 24, 2020	DecoderGraph Attention	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
Learning Fair Policies in Decentralized Cooperative Multi-Agent Reinforcement Learning	Dec 17, 2020	FairnessMulti-agent Reinforcement Learning	CodeCode Available	1
Learning Multi-Agent Communication through Structured Attentive Reasoning	Dec 1, 2020	Decision MakingDeep Reinforcement Learning	CodeCode Available	1
TLeague: A Framework for Competitive Self-Play based Distributed Multi-Agent Reinforcement Learning	Nov 25, 2020	Dota 2Multi-agent Reinforcement Learning	CodeCode Available	1
Is Independent Learning All You Need in the StarCraft Multi-Agent Challenge?	Nov 18, 2020	AllMulti-agent Reinforcement Learning	CodeCode Available	1
Scalable Reinforcement Learning Policies for Multi-Agent Control	Nov 16, 2020	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	1
Optimizing Large-Scale Fleet Management on a Road Network using Multi-Agent Deep Reinforcement Learning with Graph Neural Network	Nov 12, 2020	Deep Reinforcement LearningGraph Neural Network	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