HyperAI초신경

홈 뉴스 최신 연구 논문 튜토리얼 데이터셋 백과사전 SOTA LLM 모델 GPU 랭킹 컨퍼런스

한국어

HyperAI초신경

Smac On Smac 3S5Z Vs 3S6Z 1

평가 지표

Median Win Rate

평가 결과

이 벤치마크에서 각 모델의 성능 결과

모델 이름	Median Win Rate	Paper Title	Repository
QMIX	2	Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning
Heuristic	0	The StarCraft Multi-Agent Challenge
DIQL	62.22	DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
QMIX	67.22	DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
DDN	94.03	DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
IQL	29.83	DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
VDN	89.2	DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
DMIX	91.08	DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
DPLEX	90.62	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
QPLEX	84.38	A Unified Framework for Factorizing Distributional Value Functions for Multi-Agent Reinforcement Learning
VDN	2	The StarCraft Multi-Agent Challenge
IQL	0	The StarCraft Multi-Agent Challenge

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