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Models/MASAC

MASAC

Reported on 22 benchmarks across 2 tasks · 1 paper

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Methodology11 results

  • Multi-agent Reinforcement LearningonDef_Infantry_parallel
    Median Win Rate· 2021-04-14
    30
    best: 100 (QTRAN)
    Decomposed Soft Actor-Critic Method for Cooperative Multi-Agent Reinforcement LearningarXiv:2104.06655
  • Multi-agent Reinforcement LearningonDef_Infantry_sequential
    Median Win Rate· 2021-04-14
    37.5
    best: 100 (MADDPG)
    Decomposed Soft Actor-Critic Method for Cooperative Multi-Agent Reinforcement LearningarXiv:2104.06655
  • Multi-agent Reinforcement LearningonOff_Hard_parallel
    Median Win Rate
    0
    best: 80 (DRIMA)
  • Multi-agent Reinforcement LearningonDef_Outnumbered_sequential
    Median Win Rate
    0
    best: 100 (DRIMA)
  • Multi-agent Reinforcement LearningonOff_Complicated_parallel
    Median Win Rate
    0
    best: 100 (DRIMA)
  • Multi-agent Reinforcement LearningonOff_Near_parallel
    Median Win Rate
    0
    best: 95 (QMIX)
  • Multi-agent Reinforcement LearningonDef_Armored_parallel
    Median Win Rate
    0
    best: 90 (DMIX)
  • Multi-agent Reinforcement LearningonOff_Distant_parallel
    Median Win Rate
    0
    best: 95 (DRIMA)
  • Multi-agent Reinforcement LearningonDef_Outnumbered_parallel
    Median Win Rate
    0
    best: 70 (DRIMA)
  • Multi-agent Reinforcement LearningonDef_Armored_sequential
    Median Win Rate
    0
    best: 100 (DRIMA)
  • Multi-agent Reinforcement LearningonOff_Superhard_parallel
    Median Win Rate
    0

Playing Games11 results

  • SMAConDef_Infantry_parallel
    Median Win Rate· 2021-04-14
    30
    best: 100 (QTRAN)
    Decomposed Soft Actor-Critic Method for Cooperative Multi-Agent Reinforcement LearningarXiv:2104.06655
  • SMAConDef_Infantry_sequential
    Median Win Rate· 2021-04-14
    37.5
    best: 100 (MADDPG)
    Decomposed Soft Actor-Critic Method for Cooperative Multi-Agent Reinforcement LearningarXiv:2104.06655
  • SMAConOff_Hard_parallel
    Median Win Rate
    0
    best: 80 (DRIMA)
  • SMAConDef_Outnumbered_sequential
    Median Win Rate
    0
    best: 100 (DRIMA)
  • SMAConOff_Complicated_parallel
    Median Win Rate
    0
    best: 100 (DRIMA)
  • SMAConOff_Near_parallel
    Median Win Rate
    0
    best: 95 (QMIX)
  • SMAConDef_Armored_parallel
    Median Win Rate
    0
    best: 90 (DMIX)
  • SMAConOff_Distant_parallel
    Median Win Rate
    0
    best: 95 (DRIMA)
  • SMAConDef_Outnumbered_parallel
    Median Win Rate
    0
    best: 70 (DRIMA)
  • SMAConDef_Armored_sequential
    Median Win Rate
    0
    best: 100 (DRIMA)
  • SMAConOff_Superhard_parallel
    Median Win Rate
    0