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.

Source: Show, Describe and Conclude: On Exploiting the Structure Information of Chest X-Ray Reports

Papers

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Showing 161–170 of 1718 papers

Title	Date	Tasks	Status	Hype	Score
Randomized Entity-wise Factorization for Multi-Agent Reinforcement Learning	Jun 7, 2020	counterfactualMulti-agent Reinforcement Learning	CodeCode Available	1	5
Asynchronous Multi-Agent Reinforcement Learning for Efficient Real-Time Multi-Robot Cooperative Exploration	Jan 9, 2023	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	1	5
CTDS: Centralized Teacher with Decentralized Student for Multi-Agent Reinforcement Learning	Mar 16, 2022	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	1	5
Cross Modality 3D Navigation Using Reinforcement Learning and Neural Style Transfer	Nov 5, 2021	Computed Tomography (CT)Diagnostic	CodeCode Available	1	5
C-COMA: A CONTINUAL REINFORCEMENT LEARNING MODEL FOR DYNAMIC MULTIAGENT ENVIRONMENTS	Apr 5, 2021	Continual LearningMulti-agent Reinforcement Learning	CodeCode Available	1	5
Curriculum Learning With Counterfactual Group Relative Policy Advantage For Multi-Agent Reinforcement Learning	Jun 9, 2025	counterfactualMulti-agent Reinforcement Learning	CodeCode Available	1	5
Decomposed Soft Actor-Critic Method for Cooperative Multi-Agent Reinforcement Learning	Apr 14, 2021	counterfactualDeep Reinforcement Learning	CodeCode Available	1	5
Deep Implicit Coordination Graphs for Multi-agent Reinforcement Learning	Jun 19, 2020	Graph Neural NetworkMulti-agent Reinforcement Learning	CodeCode Available	1	5
Decentralized Social Navigation with Non-Cooperative Robots via Bi-Level Optimization	Jun 15, 2023	Collision AvoidanceMulti-agent Reinforcement Learning	CodeCode Available	1	5
IMP-MARL: a Suite of Environments for Large-scale Infrastructure Management Planning via MARL	Jun 20, 2023	BenchmarkingManagement	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