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 271–280 of 1718 papers

Title	Date	Tasks	Status	Hype
HyperMARL: Adaptive Hypernetworks for Multi-Agent RL	Dec 5, 2024	DiversityMulti-agent Reinforcement Learning	CodeCode Available	1
Learning Multi-Agent Communication through Structured Attentive Reasoning	Dec 1, 2020	Decision MakingDeep Reinforcement Learning	CodeCode Available	1
Enhancing Cooperation through Selective Interaction and Long-term Experiences in Multi-Agent Reinforcement Learning	May 4, 2024	AttributeMulti-agent Reinforcement Learning	CodeCode Available	1
Communicative Reinforcement Learning Agents for Landmark Detection in Brain Images	Aug 18, 2020	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	1
Environmental effects on emergent strategy in micro-scale multi-agent reinforcement learning	Jul 3, 2023	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	1
Episodic Multi-agent Reinforcement Learning with Curiosity-Driven Exploration	Nov 22, 2021	Efficient ExplorationMulti-agent Reinforcement Learning	CodeCode Available	1
Exponential Topology-enabled Scalable Communication in Multi-agent Reinforcement Learning	Feb 27, 2025	Multi-agent Reinforcement Learning	CodeCode Available	1
Fleet Rebalancing for Expanding Shared e-Mobility Systems: A Multi-agent Deep Reinforcement Learning Approach	Nov 11, 2022	Deep Reinforcement LearningMulti-agent Reinforcement Learning	CodeCode Available	1
Actor-Attention-Critic for Multi-Agent Reinforcement Learning	Oct 5, 2018	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	1
N-Agent Ad Hoc Teamwork	Apr 16, 2024	Autonomous DrivingMulti-agent Reinforcement Learning	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