HyperAI超神経
ホームニュース最新論文チュートリアルデータセット百科事典SOTALLMモデルGPU ランキング学会
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HyperAI超神経

Smac On Smac Off Complicated Parallel

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 TitleRepository
IQL35.0--
MASAC0.0Decomposed Soft Actor-Critic Method for Cooperative Multi-Agent Reinforcement Learning
DRIMA100Disentangling Sources of Risk for Distributional Multi-Agent Reinforcement Learning-
DMIX0.0DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
QMIX0.0QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning
COMA0.0Counterfactual Multi-Agent Policy Gradients
DDN0.0DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
VDN70.0Value-Decomposition Networks For Cooperative Multi-Agent Learning
DIQL0.0DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
QTRAN0.0QTRAN: Learning to Factorize with Transformation for Cooperative Multi-Agent Reinforcement Learning
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