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 1441–1450 of 1718 papers

Title	Date	Tasks	Status	Hype
Reinforcement Communication Learning in Different Social Network Structures	Jul 19, 2020	Multi-agent Reinforcement Learning	CodeCode Available	0
MAPS: Multi-agent Reinforcement Learning-based Portfolio Management System	Jul 10, 2020	ManagementMulti-agent Reinforcement Learning	—Unverified	0
Curriculum learning for multilevel budgeted combinatorial problems	Jul 7, 2020	Combinatorial OptimizationMulti-agent Reinforcement Learning	CodeCode Available	0
Consensus Multi-Agent Reinforcement Learning for Volt-VAR Control in Power Distribution Networks	Jul 6, 2020	Deep Reinforcement LearningManagement	—Unverified	0
Learning Implicit Credit Assignment for Cooperative Multi-Agent Reinforcement Learning	Jul 6, 2020	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	1
Reward Machines for Cooperative Multi-Agent Reinforcement Learning	Jul 3, 2020	Multi-agent Reinforcement LearningQ-Learning	CodeCode Available	1
Decentralized Deep Reinforcement Learning for Network Level Traffic Signal Control	Jul 2, 2020	Deep Reinforcement LearningMulti-agent Reinforcement Learning	—Unverified	0
R2-B2: Recursive Reasoning-Based Bayesian Optimization for No-Regret Learning in Games	Jun 30, 2020	Bayesian OptimizationMulti-agent Reinforcement Learning	—Unverified	0
Online Multi-agent Reinforcement Learning for Decentralized Inverter-based Volt-VAR Control	Jun 23, 2020	Multi-agent Reinforcement Learningreinforcement-learning	—Unverified	0
QTRAN++: Improved Value Transformation for Cooperative Multi-Agent Reinforcement Learning	Jun 22, 2020	Multi-agent Reinforcement Learningreinforcement-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