HyperAI超神经

首页资讯论文教程数据集百科 SOTA LLM 模型天梯 GPU 天梯顶会

中文

HyperAI超神经

Smac On Smac Def Infantry Sequential

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
DRIMA	100	Disentangling Sources of Risk for Distributional Multi-Agent Reinforcement Learning	-
DIQL	93.8	DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
DDN	90.6	DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
DMIX	100	DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
MADDPG	100	Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments
QTRAN	100	QTRAN: Learning to Factorize with Transformation for Cooperative Multi-Agent Reinforcement Learning
IQL	93.8	The StarCraft Multi-Agent Challenges+ : Learning of Multi-Stage Tasks and Environmental Factors without Precise Reward Functions
QMIX	96.9	QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning
COMA	28.1	Counterfactual Multi-Agent Policy Gradients
MASAC	37.5	Decomposed Soft Actor-Critic Method for Cooperative Multi-Agent Reinforcement Learning
VDN	96.9	Value-Decomposition Networks For Cooperative Multi-Agent Learning

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