HyperAI超神经
首页
资讯
最新论文
教程
数据集
百科
SOTA
LLM 模型天梯
GPU 天梯
顶会
开源项目
全站搜索
关于
中文
HyperAI超神经
Toggle sidebar
全站搜索…
⌘
K
首页
SOTA
Smac
Smac On Smac 3S5Z Vs 3S6Z 1
Smac On Smac 3S5Z Vs 3S6Z 1
评估指标
Median Win Rate
评测结果
各个模型在此基准测试上的表现结果
Columns
模型名称
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
0 of 13 row(s) selected.
Previous
Next