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 1001–1010 of 1718 papers

Title	Date	Tasks	Status
Optimization of Image Transmission in a Cooperative Semantic Communication Networks	Jan 1, 2023	Multi-agent Reinforcement LearningReinforcement Learning (RL)	—Unverified
Asynchronous Hybrid Reinforcement Learning for Latency and Reliability Optimization in the Metaverse over Wireless Communications	Dec 30, 2022	Multi-agent Reinforcement Learning	—Unverified
Decentralized Voltage Control with Peer-to-peer Energy Trading in a Distribution Network	Dec 29, 2022	energy tradingManagement	—Unverified
Learning Individual Policies in Large Multi-agent Systems through Local Variance Minimization	Dec 27, 2022	Multi-agent Reinforcement Learning	—Unverified
Strangeness-driven Exploration in Multi-Agent Reinforcement Learning	Dec 27, 2022	Efficient ExplorationMulti-agent Reinforcement Learning	CodeCode Available
Coordinated Multi-Agent Reinforcement Learning for Unmanned Aerial Vehicle Swarms in Autonomous Mobile Access Applications	Dec 23, 2022	Deep Reinforcement LearningMulti-agent Reinforcement Learning	—Unverified
Certified Policy Smoothing for Cooperative Multi-Agent Reinforcement Learning	Dec 22, 2022	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available
AdverSAR: Adversarial Search and Rescue via Multi-Agent Reinforcement Learning	Dec 20, 2022	Meta-LearningMulti-agent Reinforcement Learning	—Unverified
Bandit approach to conflict-free multi-agent Q-learning in view of photonic implementation	Dec 20, 2022	Decision MakingMulti-agent Reinforcement Learning	—Unverified
An Energy-aware and Fault-tolerant Deep Reinforcement Learning based approach for Multi-agent Patrolling Problems	Dec 16, 2022	Autonomous VehiclesDeep Reinforcement Learning	—Unverified

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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