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Smac On Smac Mmm2 1

Metrics

Median Win Rate

Results

Performance results of various models on this benchmark

Paper Title
ACE100ACE: Cooperative Multi-agent Q-learning with Bidirectional Action-Dependency
DDN97.22DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
DPLEX96.88A Unified Framework for Factorizing Distributional Value Functions for Multi-Agent Reinforcement Learning
QPLEX96.88A Unified Framework for Factorizing Distributional Value Functions for Multi-Agent Reinforcement Learning
DMIX95.11DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
QMIX92.44DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
VDN89.2DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
DIQL85.23DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
QMIX69The StarCraft Multi-Agent Challenge
QMIX69Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning
IQL68.92DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
VDN1The StarCraft Multi-Agent Challenge
IQL0The StarCraft Multi-Agent Challenge
Heuristic0The StarCraft Multi-Agent Challenge
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