HyperAI超神経

ホームニュース論文チュートリアルデータセット百科事典 SOTA LLMモデル GPU ランキング学会

サイトについて

日本語

HyperAI超神経

Smac On Smac Def Armored Sequential

評価指標

Median Win Rate

評価結果

このベンチマークにおける各モデルのパフォーマンス結果

モデル名	Median Win Rate	Paper Title	Repository
QTRAN	93.8	QTRAN: Learning to Factorize with Transformation for Cooperative Multi-Agent Reinforcement Learning
VDN	96.9	Value-Decomposition Networks For Cooperative Multi-Agent Learning
QMIX	0.0	QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning
MASAC	0.0	Decomposed Soft Actor-Critic Method for Cooperative Multi-Agent Reinforcement Learning
DRIMA	100	Disentangling Sources of Risk for Distributional Multi-Agent Reinforcement Learning	-
IQL	9.4	The StarCraft Multi-Agent Challenges+ : Learning of Multi-Stage Tasks and Environmental Factors without Precise Reward Functions
DDN	71.9	DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
COMA	0.0	Counterfactual Multi-Agent Policy Gradients
MADDPG	90.6	Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments
DIQL	53.1	DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
DMIX	81.3	DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning

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