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ホーム
SOTA
Smac
Smac On Smac Mmm2 1
Smac On Smac Mmm2 1
評価指標
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
Columns
モデル名
Median Win Rate
Paper Title
Repository
ACE
100
ACE: Cooperative Multi-agent Q-learning with Bidirectional Action-Dependency
QMIX
69
The StarCraft Multi-Agent Challenge
DIQL
85.23
DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
DPLEX
96.88
A Unified Framework for Factorizing Distributional Value Functions for Multi-Agent Reinforcement Learning
QMIX
69
Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning
IQL
0
The StarCraft Multi-Agent Challenge
VDN
1
The StarCraft Multi-Agent Challenge
QMIX
92.44
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
IQL
68.92
DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
Heuristic
0
The StarCraft Multi-Agent Challenge
DDN
97.22
DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
DMIX
95.11
DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
QPLEX
96.88
A Unified Framework for Factorizing Distributional Value Functions for Multi-Agent Reinforcement Learning
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