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Smac On Smac 6H Vs 8Z 1

Métriques

Median Win Rate

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle
Median Win Rate
Paper TitleRepository
IQL0The StarCraft Multi-Agent Challenge
VDN0DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
Heuristic0The StarCraft Multi-Agent Challenge
DDN83.92DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
QMIX3Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning
QMIX12.78DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
ACE93.75ACE: Cooperative Multi-agent Q-learning with Bidirectional Action-Dependency
VDN0The StarCraft Multi-Agent Challenge
QPLEX-A Unified Framework for Factorizing Distributional Value Functions for Multi-Agent Reinforcement Learning
QMIX3The StarCraft Multi-Agent Challenge
DMIX49.43DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
DPLEX43.75A Unified Framework for Factorizing Distributional Value Functions for Multi-Agent Reinforcement Learning
IQL0DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
DIQL0.00DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
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