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 321–330 of 1718 papers

Title	Date	Tasks	Status	Hype
QTypeMix: Enhancing Multi-Agent Cooperative Strategies through Heterogeneous and Homogeneous Value Decomposition	Aug 12, 2024	Multi-agent Reinforcement LearningSMAC	CodeCode Available	0
Enhancing Heterogeneous Multi-Agent Cooperation in Decentralized MARL via GNN-driven Intrinsic Rewards	Aug 12, 2024	Graph Neural NetworkMulti-agent Reinforcement Learning	CodeCode Available	0
Assigning Credit with Partial Reward Decoupling in Multi-Agent Proximal Policy Optimization	Aug 8, 2024	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	1
Environment Complexity and Nash Equilibria in a Sequential Social Dilemma	Aug 4, 2024	Multi-agent Reinforcement Learning	—Unverified	0
A Survey on Self-play Methods in Reinforcement Learning	Aug 2, 2024	Multi-agent Reinforcement Learningreinforcement-learning	—Unverified	0
Multi-agent reinforcement learning for the control of three-dimensional Rayleigh-Bénard convection	Jul 31, 2024	Deep Reinforcement LearningMulti-agent Reinforcement Learning	CodeCode Available	0
Architectural Influence on Variational Quantum Circuits in Multi-Agent Reinforcement Learning: Evolutionary Strategies for Optimization	Jul 30, 2024	Autonomous DrivingMulti-agent Reinforcement Learning	—Unverified	0
Quantum Computing and Neuromorphic Computing for Safe, Reliable, and explainable Multi-Agent Reinforcement Learning: Optimal Control in Autonomous Robotics	Jul 29, 2024	Multi-agent Reinforcement Learning	CodeCode Available	0
Advanced deep-reinforcement-learning methods for flow control: group-invariant and positional-encoding networks improve learning speed and quality	Jul 25, 2024	Deep Reinforcement LearningMulti-agent Reinforcement Learning	CodeCode Available	0
Reinforced Prompt Personalization for Recommendation with Large Language Models	Jul 24, 2024	Multi-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