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 261–270 of 1718 papers

Title	Date	Tasks	Status	Hype
Who2com: Collaborative Perception via Learnable Handshake Communication	Mar 21, 2020	Multi-agent Reinforcement LearningReinforcement Learning	CodeCode Available	1
FACMAC: Factored Multi-Agent Centralised Policy Gradients	Mar 14, 2020	MuJoCoMulti-agent Reinforcement Learning	CodeCode Available	1
On the Robustness of Cooperative Multi-Agent Reinforcement Learning	Mar 8, 2020	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	1
"Other-Play" for Zero-Shot Coordination	Mar 6, 2020	Multi-agent Reinforcement LearningReinforcement Learning	CodeCode Available	1
IG-RL: Inductive Graph Reinforcement Learning for Massive-Scale Traffic Signal Control	Mar 6, 2020	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	1
Learning Scalable Multi-Agent Coordination by Spatial Differentiation for Traffic Signal Control	Feb 27, 2020	Deep Reinforcement LearningGraph Attention	CodeCode Available	1
Represented Value Function Approach for Large Scale Multi Agent Reinforcement Learning	Jan 4, 2020	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	1
Simplified Action Decoder for Deep Multi-Agent Reinforcement Learning	Dec 4, 2019	DecoderMulti-agent Reinforcement Learning	CodeCode Available	1
LIIR: Learning Individual Intrinsic Reward in Multi-Agent Reinforcement Learning	Dec 1, 2019	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	1
PIC: Permutation Invariant Critic for Multi-Agent Deep Reinforcement Learning	Oct 31, 2019	Deep Reinforcement LearningMulti-agent Reinforcement 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