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 111–120 of 1718 papers

Title	Date	Tasks	Status	Hype	Score
Curriculum Learning With Counterfactual Group Relative Policy Advantage For Multi-Agent Reinforcement Learning	Jun 9, 2025	counterfactualMulti-agent Reinforcement Learning	CodeCode Available	1	5
Distributed Multi-Agent Reinforcement Learning with One-hop Neighbors and Compute Straggler Mitigation	Feb 18, 2022	Distributed ComputingMulti-agent Reinforcement Learning	CodeCode Available	1	5
Enhancing Cooperation through Selective Interaction and Long-term Experiences in Multi-Agent Reinforcement Learning	May 4, 2024	AttributeMulti-agent Reinforcement Learning	CodeCode Available	1	5
FACMAC: Factored Multi-Agent Centralised Policy Gradients	Mar 14, 2020	MuJoCoMulti-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
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
DeepFreight: Integrating Deep Reinforcement Learning and Mixed Integer Programming for Multi-transfer Truck Freight Delivery	Mar 5, 2021	Deep Reinforcement LearningMulti-agent Reinforcement Learning	CodeCode Available	1	5
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
HAD-Gen: Human-like and Diverse Driving Behavior Modeling for Controllable Scenario Generation	Mar 19, 2025	Autonomous VehiclesImitation 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