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 131–140 of 1718 papers

Title	Date	Tasks	Status	Hype	Score
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	5
Coach-Player Multi-Agent Reinforcement Learning for Dynamic Team Composition	May 18, 2021	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	1	5
FoX: Formation-aware exploration in multi-agent reinforcement learning	Aug 22, 2023	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	1	5
Agent-Temporal Attention for Reward Redistribution in Episodic Multi-Agent Reinforcement Learning	Jan 12, 2022	Multi-agent Reinforcement Learningreinforcement-learning	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
Celebrating Diversity in Shared Multi-Agent Reinforcement Learning	Jun 4, 2021	DiversityMulti-agent Reinforcement Learning	CodeCode Available	1	5
Fully Decentralized Multi-Agent Reinforcement Learning with Networked Agents	Feb 23, 2018	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	1	5
HAD-Gen: Human-like and Diverse Driving Behavior Modeling for Controllable Scenario Generation	Mar 19, 2025	Autonomous VehiclesImitation Learning	CodeCode Available	1	5
CAMMARL: Conformal Action Modeling in Multi Agent Reinforcement Learning	Jun 19, 2023	Conformal PredictionDecision Making	CodeCode Available	1	5
Actor-Attention-Critic for Multi-Agent Reinforcement Learning	Oct 5, 2018	Multi-agent Reinforcement Learningreinforcement-learning	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