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

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 1681–1690 of 1718 papers

Title	Date	Tasks	Status	Hype
Towards Learning Transferable Conversational Skills using Multi-dimensional Dialogue Modelling	Mar 31, 2018	Dialogue ManagementDomain Adaptation	CodeCode Available	0
QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning	Mar 30, 2018	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	1
Entropy based Independent Learning in Anonymous Multi-Agent Settings	Mar 27, 2018	FairnessMulti-agent Reinforcement Learning	—Unverified	0
Inequity aversion improves cooperation in intertemporal social dilemmas	Mar 23, 2018	Multi-agent Reinforcement LearningReinforcement Learning	CodeCode Available	1
Valuing knowledge, information and agency in Multi-agent Reinforcement Learning: a case study in smart buildings	Mar 9, 2018	Multi-agent Reinforcement LearningReinforcement Learning	—Unverified	0
Intent-aware Multi-agent Reinforcement Learning	Mar 6, 2018	Multi-agent Reinforcement Learningreinforcement-learning	—Unverified	0
Real-Time Bidding with Multi-Agent Reinforcement Learning in Display Advertising	Feb 27, 2018	ClusteringMulti-agent Reinforcement Learning	—Unverified	0
Modeling Others using Oneself in Multi-Agent Reinforcement Learning	Feb 26, 2018	Multi-agent Reinforcement Learningreinforcement-learning	—Unverified	0
Fully Decentralized Multi-Agent Reinforcement Learning with Networked Agents	Feb 23, 2018	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	1
Asynchronous stochastic approximations with asymptotically biased errors and deep multi-agent learning	Feb 22, 2018	Multi-agent Reinforcement LearningPolicy Gradient Methods	—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