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Smac On Smac Corridor

Métriques

Average Score

Median Win Rate

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle	Average Score	Median Win Rate	Paper Title	Repository
DIQL	19.68	91.62	DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning	-
DPLEX	19.08	81.25	A Unified Framework for Factorizing Distributional Value Functions for Multi-Agent Reinforcement Learning	-
VDN	19.47	85.34	DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning	-
IQL	-	0	The StarCraft Multi-Agent Challenge	-
DDN	20	95.4	DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning	-
Heuristic	-	0	The StarCraft Multi-Agent Challenge	-
QMIX	15.07	37.61	DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning	-
DMIX	19.66	90.45	DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning	-
QPLEX	18.73	75.00	A Unified Framework for Factorizing Distributional Value Functions for Multi-Agent Reinforcement Learning	-
ACE	-	100	ACE: Cooperative Multi-agent Q-learning with Bidirectional Action-Dependency	-
QMIX	-	1	Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning	-
QMIX	-	1	The StarCraft Multi-Agent Challenge	-
IQL	19.42	84.87	DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning	-

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