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 1381–1390 of 1718 papers

Title	Date	Tasks	Status	Hype
Emergent Reciprocity and Team Formation from Randomized Uncertain Social Preferences	Nov 10, 2020	Multi-agent Reinforcement Learning	CodeCode Available	2
Multi-Agent Reinforcement Learning for Channel Assignment and Power Allocation in Platoon-Based C-V2X Systems	Nov 9, 2020	Autonomous VehiclesMulti-agent Reinforcement Learning	—Unverified	0
Single and Multi-Agent Deep Reinforcement Learning for AI-Enabled Wireless Networks: A Tutorial	Nov 6, 2020	Decision MakingDeep Reinforcement Learning	—Unverified	0
Learning a Decentralized Multi-arm Motion Planner	Nov 5, 2020	Motion PlanningMulti-agent Reinforcement Learning	CodeCode Available	1
LQR with Tracking: A Zeroth-order Approach and Its Global Convergence	Nov 3, 2020	Multi-agent Reinforcement Learning	—Unverified	0
Multi-Agent Reinforcement Learning for Visibility-based Persistent Monitoring	Nov 2, 2020	Graph AttentionMulti-agent Reinforcement Learning	CodeCode Available	0
Interpreting Graph Drawing with Multi-Agent Reinforcement Learning	Nov 2, 2020	Multi-agent Reinforcement Learningreinforcement-learning	—Unverified	0
Game-Theoretic Multiagent Reinforcement Learning	Nov 1, 2020	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	1
Online Learning in Unknown Markov Games	Oct 28, 2020	Multi-agent Reinforcement Learning	—Unverified	0
Succinct and Robust Multi-Agent Communication With Temporal Message Control	Oct 27, 2020	Multi-agent Reinforcement LearningReinforcement Learning (RL)	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