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 221–230 of 1718 papers

Title	Date	Tasks	Status	Hype
Phantom -- A RL-driven multi-agent framework to model complex systems	Oct 12, 2022	Decision MakingMulti-agent Reinforcement Learning	CodeCode Available	1
PIC: Permutation Invariant Critic for Multi-Agent Deep Reinforcement Learning	Oct 31, 2019	Deep Reinforcement LearningMulti-agent Reinforcement Learning	CodeCode Available	1
Progression Cognition Reinforcement Learning with Prioritized Experience for Multi-Vehicle Pursuit	Jun 8, 2023	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	1
PyTAG: Tabletop Games for Multi-Agent Reinforcement Learning	May 28, 2024	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	1
QGNN: Value Function Factorisation with Graph Neural Networks	May 25, 2022	Graph Neural NetworkMulti-agent Reinforcement Learning	CodeCode Available	1
QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning	Mar 30, 2018	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	1
An Extended Benchmarking of Multi-Agent Reinforcement Learning Algorithms in Complex Fully Cooperative Tasks	Feb 7, 2025	BenchmarkingMulti-agent Reinforcement Learning	CodeCode Available	1
Cooperative Policy Learning with Pre-trained Heterogeneous Observation Representations	Dec 24, 2020	DecoderGraph Attention	CodeCode Available	1
C-COMA: A CONTINUAL REINFORCEMENT LEARNING MODEL FOR DYNAMIC MULTIAGENT ENVIRONMENTS	Apr 5, 2021	Continual LearningMulti-agent Reinforcement Learning	CodeCode Available	1
Cross Modality 3D Navigation Using Reinforcement Learning and Neural Style Transfer	Nov 5, 2021	Computed Tomography (CT)Diagnostic	CodeCode Available	1

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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