HyperAI超神经

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中文

HyperAI超神经

Smac On Smac Def Armored Parallel

评估指标

Median Win Rate

评测结果

各个模型在此基准测试上的表现结果

模型名称	Median Win Rate	Paper Title	Repository
DMIX	90.0	DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
COMA	0.0	Counterfactual Multi-Agent Policy Gradients
DDN	0.0	DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
QMIX	75.0	QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning
DRIMA	60.0	Disentangling Sources of Risk for Distributional Multi-Agent Reinforcement Learning	-
DIQL	0.0	DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
IQL	0.0	The StarCraft Multi-Agent Challenges+ : Learning of Multi-Stage Tasks and Environmental Factors without Precise Reward Functions
MASAC	0.0	Decomposed Soft Actor-Critic Method for Cooperative Multi-Agent Reinforcement Learning
QTRAN	5.0	QTRAN: Learning to Factorize with Transformation for Cooperative Multi-Agent Reinforcement Learning
VDN	5.0	Value-Decomposition Networks For Cooperative Multi-Agent Learning

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Smac On Smac Def Armored Parallel | SOTA | HyperAI超神经