HyperAIHyperAI

Command Palette

Search for a command to run...

Console

Smac On Smac 6H Vs 8Z 1

Metrics

Median Win Rate

Results

Performance results of various models on this benchmark

Paper Title
ACE93.75ACE: Cooperative Multi-agent Q-learning with Bidirectional Action-Dependency
DDN83.92DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
DMIX49.43DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
DPLEX43.75A Unified Framework for Factorizing Distributional Value Functions for Multi-Agent Reinforcement Learning
QMIX12.78DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
QMIX3Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning
QMIX3The StarCraft Multi-Agent Challenge
IQL0The StarCraft Multi-Agent Challenge
VDN0DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
Heuristic0The StarCraft Multi-Agent Challenge
VDN0The StarCraft Multi-Agent Challenge
IQL0DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
DIQL0.00DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
QPLEX-A Unified Framework for Factorizing Distributional Value Functions for Multi-Agent Reinforcement Learning
0 of 14 row(s) selected.
Smac On Smac 6H Vs 8Z 1 | SOTA | HyperAI