HyperAI
الرئيسية
الأخبار
أحدث الأوراق البحثية
الدروس
مجموعات البيانات
الموسوعة
SOTA
نماذج LLM
لوحة الأداء GPU
الفعاليات
البحث
حول
العربية
HyperAI
Toggle sidebar
البحث في الموقع...
⌘
K
الرئيسية
SOTA
Smac
Smac On Smac 6H Vs 8Z 1
Smac On Smac 6H Vs 8Z 1
المقاييس
Median Win Rate
النتائج
نتائج أداء النماذج المختلفة على هذا المعيار القياسي
Columns
اسم النموذج
Median Win Rate
Paper Title
Repository
IQL
0
The StarCraft Multi-Agent Challenge
VDN
0
DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
Heuristic
0
The StarCraft Multi-Agent Challenge
DDN
83.92
DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
QMIX
3
Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning
QMIX
12.78
DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
ACE
93.75
ACE: Cooperative Multi-agent Q-learning with Bidirectional Action-Dependency
VDN
0
The StarCraft Multi-Agent Challenge
QPLEX
-
A Unified Framework for Factorizing Distributional Value Functions for Multi-Agent Reinforcement Learning
QMIX
3
The StarCraft Multi-Agent Challenge
DMIX
49.43
DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
DPLEX
43.75
A Unified Framework for Factorizing Distributional Value Functions for Multi-Agent Reinforcement Learning
IQL
0
DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
DIQL
0.00
DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
0 of 14 row(s) selected.
Previous
Next