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.

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Papers

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Showing 211–220 of 1718 papers

Title	Date	Tasks	Status	Hype
The Surprising Effectiveness of PPO in Cooperative, Multi-Agent Games	Mar 2, 2021	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	1
Multi-agent Reinforcement Learning in OpenSpiel: A Reproduction Report	Feb 27, 2021	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	1
Multi-Agent Reinforcement Learning of 3D Furniture Layout Simulation in Indoor Graphics Scenes	Feb 18, 2021	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	1
DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning	Feb 16, 2021	Multi-agent Reinforcement LearningQ-Learning	CodeCode Available	1
Intelligent Electric Vehicle Charging Recommendation Based on Multi-Agent Reinforcement Learning	Feb 15, 2021	Deep Reinforcement LearningMulti-agent Reinforcement Learning	CodeCode Available	1
Scaling Multi-Agent Reinforcement Learning with Selective Parameter Sharing	Feb 15, 2021	Deep Reinforcement LearningMulti-agent Reinforcement Learning	CodeCode Available	1
Rethinking the Implementation Matters in Cooperative Multi-Agent Reinforcement Learning	Feb 6, 2021	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	1
Multi-Agent Reinforcement Learning with Temporal Logic Specifications	Feb 1, 2021	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	1
UPDeT: Universal Multi-agent Reinforcement Learning via Policy Decoupling with Transformers	Jan 20, 2021	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	1
MetaVIM: Meta Variationally Intrinsic Motivated Reinforcement Learning for Decentralized Traffic Signal Control	Jan 4, 2021	Deep Reinforcement LearningMeta-Learning	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