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 141–150 of 1718 papers

Title	Date	Tasks	Status	Hype	Score
C-COMA: A CONTINUAL REINFORCEMENT LEARNING MODEL FOR DYNAMIC MULTIAGENT ENVIRONMENTS	Apr 5, 2021	Continual LearningMulti-agent Reinforcement Learning	CodeCode Available	1	5
Celebrating Diversity in Shared Multi-Agent Reinforcement Learning	Jun 4, 2021	DiversityMulti-agent Reinforcement Learning	CodeCode Available	1	5
Beyond Greedy Search: Tracking by Multi-Agent Reinforcement Learning-based Beam Search	May 19, 2022	Decision MakingImage Captioning	CodeCode Available	1	5
FoX: Formation-aware exploration in multi-agent reinforcement learning	Aug 22, 2023	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	1	5
Bayesian Action Decoder for Deep Multi-Agent Reinforcement Learning	Nov 4, 2018	DecoderMulti-agent Reinforcement Learning	CodeCode Available	1	5
CityLearn: Standardizing Research in Multi-Agent Reinforcement Learning for Demand Response and Urban Energy Management	Dec 18, 2020	energy managementManagement	CodeCode Available	1	5
Scalable Multi-agent Reinforcement Learning Algorithm for Wireless Networks	Aug 1, 2021	Decision MakingMulti-agent Reinforcement Learning	CodeCode Available	1	5
Coach-Player Multi-Agent Reinforcement Learning for Dynamic Team Composition	May 18, 2021	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	1	5
CoLight: Learning Network-level Cooperation for Traffic Signal Control	May 11, 2019	Multi-agent Reinforcement LearningReinforcement Learning	CodeCode Available	1	5
Battlesnake Challenge: A Multi-agent Reinforcement Learning Playground with Human-in-the-loop	Jul 20, 2020	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	1	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