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 1651–1660 of 1718 papers

Title	Date	Tasks	Status	Hype
Multi-agent Deep Reinforcement Learning with Extremely Noisy Observations	Dec 3, 2018	Deep Reinforcement LearningMulti-agent Reinforcement Learning	—Unverified	0
Deep Multi-Agent Reinforcement Learning with Relevance Graphs	Nov 30, 2018	Deep Reinforcement LearningMulti-agent Reinforcement Learning	CodeCode Available	0
Emergence of linguistic conventions in multi-agent reinforcement learning	Nov 17, 2018	Multi-agent Reinforcement Learningreinforcement-learning	—Unverified	0
Coordinating Disaster Emergency Response with Heuristic Reinforcement Learning	Nov 12, 2018	Multi-agent Reinforcement Learningreinforcement-learning	—Unverified	0
Bayesian Action Decoder for Deep Multi-Agent Reinforcement Learning	Nov 4, 2018	DecoderMulti-agent Reinforcement Learning	CodeCode Available	1
Multi-Agent Common Knowledge Reinforcement Learning	Oct 27, 2018	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	0
TarMAC: Targeted Multi-Agent Communication	Oct 26, 2018	Multi-agent Reinforcement LearningReinforcement Learning	—Unverified	0
Multi-Agent Reinforcement Learning Based Resource Allocation for UAV Networks	Oct 24, 2018	Multi-agent Reinforcement LearningQ-Learning	—Unverified	0
Multi-Agent Actor-Critic with Generative Cooperative Policy Network	Oct 22, 2018	Multi-agent Reinforcement LearningReinforcement Learning	—Unverified	0
Social Influence as Intrinsic Motivation for Multi-Agent Deep Reinforcement Learning	Oct 19, 2018	counterfactualCounterfactual Reasoning	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