الرئيسية الأخبار أحدث الأوراق البحثية الدروس مجموعات البيانات الموسوعة SOTA نماذج LLM لوحة الأداء GPU الفعاليات

العربية

Smac On Smac 27M Vs 30M

المقاييس

Average Score

Median Win Rate

النتائج

نتائج أداء النماذج المختلفة على هذا المعيار القياسي

اسم النموذج	Average Score	Median Win Rate	Paper Title	Repository
DMIX	19.43	85.45	DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning	-
VDN	18.45	63.12	DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning	-
DIQL	14.45	6.02	DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning	-
QMIX	19.41	84.77	DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning	-
Heuristic	-	0	The StarCraft Multi-Agent Challenge	-
DDN	19.71	91.48	DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning	-
QPLEX	19.33	78.12	A Unified Framework for Factorizing Distributional Value Functions for Multi-Agent Reinforcement Learning	-
DPLEX	19.62	90.62	A Unified Framework for Factorizing Distributional Value Functions for Multi-Agent Reinforcement Learning	-
IQL	14.01	2.27	DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning	-
QMIX	-	49	The StarCraft Multi-Agent Challenge	-
QMIX	-	49	Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning	-

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Smac On Smac 27M Vs 30M | SOTA | HyperAI