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 1421–1430 of 1718 papers

Title	Date	Tasks	Status	Hype
Learning Nash Equilibria in Zero-Sum Stochastic Games via Entropy-Regularized Policy Approximation	Sep 1, 2020	Multi-agent Reinforcement LearningQ-Learning	—Unverified	0
Learning to Collaborate in Multi-Module Recommendation via Multi-Agent Reinforcement Learning without Communication	Aug 21, 2020	Multi-agent Reinforcement LearningReinforcement Learning (RL)	—Unverified	0
BGC: Multi-Agent Group Belief with Graph Clustering	Aug 20, 2020	ClusteringGraph Clustering	—Unverified	0
Optimal control towards sustainable wastewater treatment plants based on multi-agent reinforcement learning	Aug 19, 2020	Deep Reinforcement LearningMulti-agent Reinforcement Learning	CodeCode Available	1
Towards Closing the Sim-to-Real Gap in Collaborative Multi-Robot Deep Reinforcement Learning	Aug 18, 2020	Deep Reinforcement LearningMulti-agent Reinforcement Learning	CodeCode Available	0
On the Convergence of Consensus Algorithms with Markovian Noise and Gradient Bias	Aug 18, 2020	Multi-agent Reinforcement Learning	—Unverified	0
Communicative Reinforcement Learning Agents for Landmark Detection in Brain Images	Aug 18, 2020	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	1
The reinforcement learning-based multi-agent cooperative approach for the adaptive speed regulation on a metallurgical pickling line	Aug 16, 2020	Multi-agent Reinforcement LearningOffline RL	—Unverified	0
REMAX: Relational Representation for Multi-Agent Exploration	Aug 12, 2020	Multi-agent Reinforcement Learning	—Unverified	0
Distributed Deep Reinforcement Learning for Functional Split Control in Energy Harvesting Virtualized Small Cells	Aug 7, 2020	Deep Reinforcement LearningMulti-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