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 891–900 of 1718 papers

Title	Date	Tasks	Status	Hype
Distributional Reward Estimation for Effective Multi-Agent Deep Reinforcement Learning	Oct 14, 2022	Deep Reinforcement LearningMulti-agent Reinforcement Learning	CodeCode Available	0
Personalized Federated Hypernetworks for Privacy Preservation in Multi-Task Reinforcement Learning	Oct 13, 2022	Federated LearningMulti-agent Reinforcement Learning	—Unverified	0
Towards Multi-Agent Reinforcement Learning driven Over-The-Counter Market Simulations	Oct 13, 2022	Deep Reinforcement LearningMulti-agent Reinforcement Learning	—Unverified	0
Phantom -- A RL-driven multi-agent framework to model complex systems	Oct 12, 2022	Decision MakingMulti-agent Reinforcement Learning	CodeCode Available	1
Centralized Training with Hybrid Execution in Multi-Agent Reinforcement Learning	Oct 12, 2022	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	0
MARLlib: A Scalable and Efficient Multi-agent Reinforcement Learning Library	Oct 11, 2022	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	3
Digital Twin-Based Multiple Access Optimization and Monitoring via Model-Driven Bayesian Learning	Oct 11, 2022	Anomaly DetectionMulti-agent Reinforcement Learning	CodeCode Available	0
Multiagent Reinforcement Learning Based on Fusion-Multiactor-Attention-Critic for Multiple-Unmanned-Aerial-Vehicle Navigation Control	Oct 10, 2022	Deep Reinforcement LearningMulti-agent Reinforcement Learning	CodeCode Available	1
Learning Explicit Credit Assignment for Cooperative Multi-Agent Reinforcement Learning via Polarization Policy Gradient	Oct 10, 2022	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	0
ELIGN: Expectation Alignment as a Multi-Agent Intrinsic Reward	Oct 9, 2022	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