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 31–40 of 1718 papers

Title	Date	Tasks	Status	Hype
Heterogeneous Multi-Robot Reinforcement Learning	Jan 17, 2023	Graph Neural NetworkMulti-agent Reinforcement Learning	CodeCode Available	2
SMACv2: An Improved Benchmark for Cooperative Multi-Agent Reinforcement Learning	Dec 14, 2022	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	2
ACE: Cooperative Multi-agent Q-learning with Bidirectional Action-Dependency	Nov 29, 2022	Decision MakingMulti-agent Reinforcement Learning	CodeCode Available	2
Pareto Actor-Critic for Equilibrium Selection in Multi-Agent Reinforcement Learning	Sep 28, 2022	Graph Neural NetworkMulti-agent Reinforcement Learning	CodeCode Available	2
Deep Reinforcement Learning for Multi-Agent Interaction	Aug 2, 2022	BIG-bench Machine LearningCausal Inference	CodeCode Available	2
VMAS: A Vectorized Multi-Agent Simulator for Collective Robot Learning	Jul 7, 2022	BenchmarkingMulti-agent Reinforcement Learning	CodeCode Available	2
Multi-Agent Reinforcement Learning is a Sequence Modeling Problem	May 30, 2022	Decision MakingMuJoCo	CodeCode Available	2
Coordinate-Aligned Multi-Camera Collaboration for Active Multi-Object Tracking	Feb 22, 2022	Multi-agent Reinforcement LearningMulti-Object Tracking	CodeCode Available	2
MetaDrive: Composing Diverse Driving Scenarios for Generalizable Reinforcement Learning	Sep 26, 2021	BenchmarkingDecision Making	CodeCode Available	2
DouZero: Mastering DouDizhu with Self-Play Deep Reinforcement Learning	Jun 11, 2021	Card GamesDeep Reinforcement Learning	CodeCode Available	2

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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