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

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 11–20 of 1718 papers

Title	Date	Tasks	Status	Hype
A New Approach to Solving SMAC Task: Generating Decision Tree Code from Large Language Models	Oct 21, 2024	Decision MakingMulti-agent Reinforcement Learning	CodeCode Available	2
Heterogeneous Multi-Robot Reinforcement Learning	Jan 17, 2023	Graph Neural NetworkMulti-agent Reinforcement Learning	CodeCode Available	2
Improving Retrieval-Augmented Generation through Multi-Agent Reinforcement Learning	Jan 25, 2025	Answer GenerationMulti-agent Reinforcement Learning	CodeCode Available	2
IntersectionZoo: Eco-driving for Benchmarking Multi-Agent Contextual Reinforcement Learning	Oct 19, 2024	BenchmarkingMulti-agent Reinforcement Learning	CodeCode Available	2
Efficient Episodic Memory Utilization of Cooperative Multi-Agent Reinforcement Learning	Mar 2, 2024	DecoderMulti-agent Reinforcement Learning	CodeCode Available	2
Ensembling Prioritized Hybrid Policies for Multi-agent Pathfinding	Mar 12, 2024	Multi-Agent Path FindingMulti-agent Reinforcement Learning	CodeCode Available	2
Digital Twin Vehicular Edge Computing Network: Task Offloading and Resource Allocation	Jul 16, 2024	Edge-computingMulti-agent Reinforcement Learning	CodeCode Available	2
Developing A Multi-Agent and Self-Adaptive Framework with Deep Reinforcement Learning for Dynamic Portfolio Risk Management	Feb 1, 2024	Deep Reinforcement LearningManagement	CodeCode Available	2
AdaSociety: An Adaptive Environment with Social Structures for Multi-Agent Decision-Making	Nov 6, 2024	Decision MakingDiversity	CodeCode Available	2
Coordinate-Aligned Multi-Camera Collaboration for Active Multi-Object Tracking	Feb 22, 2022	Multi-agent Reinforcement LearningMulti-Object Tracking	CodeCode Available	2

Show:10 25 50

← PrevPage 2 of 172Next →

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