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.

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Papers

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Showing 841–850 of 1718 papers

Title	Date	Tasks	Status	Hype
Bandit approach to conflict-free multi-agent Q-learning in view of photonic implementation	Dec 20, 2022	Decision MakingMulti-agent Reinforcement Learning	—Unverified	0
An Energy-aware and Fault-tolerant Deep Reinforcement Learning based approach for Multi-agent Patrolling Problems	Dec 16, 2022	Autonomous VehiclesDeep Reinforcement Learning	—Unverified	0
Distributed-Training-and-Execution Multi-Agent Reinforcement Learning for Power Control in HetNet	Dec 15, 2022	Deep Reinforcement LearningMulti-agent Reinforcement Learning	CodeCode Available	0
Multi-Agent Reinforcement Learning with Shared Resources for Inventory Management	Dec 15, 2022	ManagementMulti-agent Reinforcement Learning	—Unverified	0
SMACv2: An Improved Benchmark for Cooperative Multi-Agent Reinforcement Learning	Dec 14, 2022	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	2
Hierarchical Strategies for Cooperative Multi-Agent Reinforcement Learning	Dec 14, 2022	Graph AttentionMulti-agent Reinforcement Learning	—Unverified	0
Scalable and Sample Efficient Distributed Policy Gradient Algorithms in Multi-Agent Networked Systems	Dec 13, 2022	Multi-agent Reinforcement Learningreinforcement-learning	—Unverified	0
Enabling the Wireless Metaverse via Semantic Multiverse Communication	Dec 13, 2022	Multi-agent Reinforcement LearningSemantic Communication	—Unverified	0
Effects of Spectral Normalization in Multi-agent Reinforcement Learning	Dec 10, 2022	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	0
What is the Solution for State-Adversarial Multi-Agent Reinforcement Learning?	Dec 6, 2022	Deep Reinforcement LearningMulti-agent Reinforcement Learning	CodeCode Available	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