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 881–890 of 1718 papers

Title	Date	Tasks	Status	Hype
Teal: Learning-Accelerated Optimization of WAN Traffic Engineering	Oct 25, 2022	Graph Neural NetworkMulti-agent Reinforcement Learning	CodeCode Available	1
How Bad is Selfish Driving? Bounding the Inefficiency of Equilibria in Urban Driving Games	Oct 24, 2022	Multi-agent Reinforcement Learning	—Unverified	0
Classifying Ambiguous Identities in Hidden-Role Stochastic Games with Multi-Agent Reinforcement Learning	Oct 24, 2022	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	0
Solving Continuous Control via Q-learning	Oct 22, 2022	continuous-controlContinuous Control	CodeCode Available	1
Collaborative Reasoning on Multi-Modal Semantic Graphs for Video-Grounded Dialogue Generation	Oct 22, 2022	Dialogue GenerationMulti-agent Reinforcement Learning	—Unverified	0
Oracles & Followers: Stackelberg Equilibria in Deep Multi-Agent Reinforcement Learning	Oct 19, 2022	Multi-agent Reinforcement Learningreinforcement-learning	—Unverified	0
Proximal Learning With Opponent-Learning Awareness	Oct 18, 2022	Multi-agent Reinforcement Learning	CodeCode Available	0
RPM: Generalizable Behaviors for Multi-Agent Reinforcement Learning	Oct 18, 2022	Multi-agent Reinforcement Learningreinforcement-learning	—Unverified	0
PTDE: Personalized Training with Distilled Execution for Multi-Agent Reinforcement Learning	Oct 17, 2022	Learning-To-RankMulti-agent Reinforcement Learning	—Unverified	0
Multi-Agent Automated Machine Learning	Oct 17, 2022	AutoMLData Augmentation	—Unverified	0

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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