HyperAI超神経

ホームニュース最新論文チュートリアルデータセット百科事典 SOTA LLMモデル GPU ランキング学会

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HyperAI超神経

Smac On Smac 27M Vs 30M

評価指標

Average Score

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	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	-

0 of 11 row(s) selected.

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