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 1641–1650 of 1718 papers

Title	Date	Tasks	Status
Deep Multi-Agent Reinforcement Learning with Discrete-Continuous Hybrid Action Spaces	Mar 12, 2019	Deep Reinforcement LearningMulti-agent Reinforcement Learning	—Unverified
Concurrent Meta Reinforcement Learning	Mar 7, 2019	Efficient ExplorationMeta-Learning	CodeCode Available
Can Sophisticated Dispatching Strategy Acquired by Reinforcement Learning? - A Case Study in Dynamic Courier Dispatching System	Mar 7, 2019	Multi-agent Reinforcement LearningReinforcement Learning	—Unverified
Message-Dropout: An Efficient Training Method for Multi-Agent Deep Reinforcement Learning	Feb 18, 2019	Deep Reinforcement LearningMulti-agent Reinforcement Learning	—Unverified
Whole-Chain Recommendations	Feb 11, 2019	Multi-agent Reinforcement LearningRecommendation Systems	—Unverified
Partner Selection for the Emergence of Cooperation in Multi-Agent Systems Using Reinforcement Learning	Feb 8, 2019	Multi-agent Reinforcement LearningReinforcement Learning	—Unverified
Reinforcement Learning from Hierarchical Critics	Feb 8, 2019	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available
Decentralized Multi-Agents by Imitation of a Centralized Controller	Feb 6, 2019	Imitation LearningMulti-agent Reinforcement Learning	—Unverified
Learning to Schedule Communication in Multi-agent Reinforcement Learning	Feb 5, 2019	Deep Reinforcement LearningMulti-agent Reinforcement Learning	CodeCode Available
What is Local Optimality in Nonconvex-Nonconcave Minimax Optimization?	Feb 2, 2019	BIG-bench Machine LearningMulti-agent Reinforcement Learning	CodeCode Available

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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