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Smac On Smac 3S5Z Vs 3S6Z 1

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
QMIX2Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning-
Heuristic0The StarCraft Multi-Agent Challenge-
DIQL62.22DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning-
QMIX67.22DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning-
DDN94.03DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning-
IQL29.83DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning-
VDN89.2DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning-
DMIX91.08DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning-
DPLEX90.62A Unified Framework for Factorizing Distributional Value Functions for Multi-Agent Reinforcement Learning-
ACE100ACE: Cooperative Multi-agent Q-learning with Bidirectional Action-Dependency-
QPLEX84.38A Unified Framework for Factorizing Distributional Value Functions for Multi-Agent Reinforcement Learning-
VDN2The StarCraft Multi-Agent Challenge-
IQL0The StarCraft Multi-Agent Challenge-
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Smac On Smac 3S5Z Vs 3S6Z 1 | SOTA | HyperAI超神経