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SOTA
Smac 1
Smac On Smac Def Infantry Parallel
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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
DIQL
45.0
DFANet: Deep Feature Aggregation for Real-Time Semantic Segmentation
DMIX
90.0
DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
IQL
40.0
The StarCraft Multi-Agent Challenges+ : Learning of Multi-Stage Tasks and Environmental Factors without Precise Reward Functions
COMA
50.0
Counterfactual Multi-Agent Policy Gradients
DDN
20.0
DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
QTRAN
100.0
QTRAN: Learning to Factorize with Transformation for Cooperative Multi-Agent Reinforcement Learning
DRIMA
100.0
Disentangling Sources of Risk for Distributional Multi-Agent Reinforcement Learning
-
QMIX
95.0
QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning
MASAC
30.0
Decomposed Soft Actor-Critic Method for Cooperative Multi-Agent Reinforcement Learning
VDN
95.0
Value-Decomposition Networks For Cooperative Multi-Agent Learning
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