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Models/DDN

DDN

Reported on 70 benchmarks across 4 tasks · 2 papers · 34 SOTA

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

Methodology35 results

Multi-agent Reinforcement LearningonSMAC 6h_vs_9z
Average Score· 2023-06-04
16
SOTA
A Unified Framework for Factorizing Distributional Value Functions for Multi-Agent Reinforcement Learning arXiv:2306.02430
Multi-agent Reinforcement LearningonSMAC 3s5z_vs_4s6z
Average Score· 2023-06-04
19.65
SOTA
A Unified Framework for Factorizing Distributional Value Functions for Multi-Agent Reinforcement Learning arXiv:2306.02430
Multi-agent Reinforcement LearningonSMAC 3s5z_vs_4s6z
Median Win Rate· 2023-06-04
89.77
SOTA
A Unified Framework for Factorizing Distributional Value Functions for Multi-Agent Reinforcement Learning arXiv:2306.02430
Multi-agent Reinforcement LearningonSMAC MMM2_7m2M1M_vs_8m4M1M
Average Score· 2023-06-04
16.5
SOTA
A Unified Framework for Factorizing Distributional Value Functions for Multi-Agent Reinforcement Learning arXiv:2306.02430
Multi-agent Reinforcement LearningonSMAC corridor_2z_vs_24zg
Average Score· 2023-06-04
11.1
SOTA
A Unified Framework for Factorizing Distributional Value Functions for Multi-Agent Reinforcement Learning arXiv:2306.02430
Multi-agent Reinforcement LearningonSMAC corridor_2z_vs_24zg
Median Win Rate· 2023-06-04
41.19
SOTA
A Unified Framework for Factorizing Distributional Value Functions for Multi-Agent Reinforcement Learning arXiv:2306.02430
Multi-agent Reinforcement LearningonSMAC MMM2_7m2M1M_vs_9m3M1M
Average Score· 2023-06-04
19.45
SOTA
A Unified Framework for Factorizing Distributional Value Functions for Multi-Agent Reinforcement Learning arXiv:2306.02430
Multi-agent Reinforcement LearningonSMAC 3s5z_vs_3s6z
Average Score· 2021-02-16
20.94
SOTA
DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning arXiv:2102.07936
Multi-agent Reinforcement LearningonSMAC 3s5z_vs_3s6z
Median Win Rate· 2021-02-16
94.03
best: 100 (ACE)
SOTA
DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning arXiv:2102.07936
Multi-agent Reinforcement LearningonSMAC corridor
Average Score· 2021-02-16
20
SOTA
DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning arXiv:2102.07936
Multi-agent Reinforcement LearningonSMAC corridor
Median Win Rate· 2021-02-16
95.4
best: 100 (ACE)
SOTA
DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning arXiv:2102.07936
Multi-agent Reinforcement LearningonSMAC MMM2
Average Score· 2021-02-16
20.9
SOTA
DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning arXiv:2102.07936
Multi-agent Reinforcement LearningonSMAC MMM2
Median Win Rate· 2021-02-16
97.22
best: 100 (ACE)
SOTA
DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning arXiv:2102.07936
Multi-agent Reinforcement LearningonSMAC 6h_vs_8z
Average Score· 2021-02-16
19.4
SOTA
DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning arXiv:2102.07936
Multi-agent Reinforcement LearningonSMAC 6h_vs_8z
Median Win Rate· 2021-02-16
83.92
best: 93.75 (ACE)
SOTA
DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning arXiv:2102.07936
Multi-agent Reinforcement LearningonSMAC 27m_vs_30m
Average Score· 2021-02-16
19.71
SOTA
DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning arXiv:2102.07936
Multi-agent Reinforcement LearningonSMAC 27m_vs_30m
Median Win Rate· 2021-02-16
91.48
SOTA
DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning arXiv:2102.07936
Multi-agent Reinforcement LearningonSMAC 6h_vs_9z
Median Win Rate· 2023-06-04
0.28
best: 1.14 (QMIX)
A Unified Framework for Factorizing Distributional Value Functions for Multi-Agent Reinforcement Learning arXiv:2306.02430
Multi-agent Reinforcement LearningonSMAC MMM2_7m2M1M_vs_8m4M1M
Median Win Rate· 2023-06-04
56.82
best: 63.35 (DMIX)
A Unified Framework for Factorizing Distributional Value Functions for Multi-Agent Reinforcement Learning arXiv:2306.02430
Multi-agent Reinforcement LearningonSMAC MMM2_7m2M1M_vs_9m3M1M
Median Win Rate· 2023-06-04
90.34
best: 92.33 (DMIX)
A Unified Framework for Factorizing Distributional Value Functions for Multi-Agent Reinforcement Learning arXiv:2306.02430
Multi-agent Reinforcement LearningonSMAC 26m_vs_30m
Average Score· 2023-06-04
18.49
best: 19.17 (DMIX)
A Unified Framework for Factorizing Distributional Value Functions for Multi-Agent Reinforcement Learning arXiv:2306.02430
Multi-agent Reinforcement LearningonSMAC 26m_vs_30m
Median Win Rate· 2023-06-04
67.9
best: 81.82 (DMIX)
A Unified Framework for Factorizing Distributional Value Functions for Multi-Agent Reinforcement Learning arXiv:2306.02430
Multi-agent Reinforcement LearningonDef_Infantry_parallel
Median Win Rate· 2021-02-16
20
best: 100 (QTRAN)
DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning arXiv:2102.07936
Multi-agent Reinforcement LearningonDef_Armored_sequential
Median Win Rate· 2021-02-16
71.9
best: 100 (DRIMA)
DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning arXiv:2102.07936
Multi-agent Reinforcement LearningonDef_Infantry_sequential
Median Win Rate· 2021-02-16
90.6
best: 100 (MADDPG)
DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning arXiv:2102.07936
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 LearningonOff_Superhard_parallel
Median Win Rate
0
2D Object DetectiononUDED
ODS
0.832
2D Object DetectiononBIPED
ODS
0.916

Playing Games33 results

SMAConSMAC 6h_vs_9z
Average Score· 2023-06-04
16
SOTA
A Unified Framework for Factorizing Distributional Value Functions for Multi-Agent Reinforcement Learning arXiv:2306.02430
SMAConSMAC 3s5z_vs_4s6z
Average Score· 2023-06-04
19.65
SOTA
A Unified Framework for Factorizing Distributional Value Functions for Multi-Agent Reinforcement Learning arXiv:2306.02430
SMAConSMAC 3s5z_vs_4s6z
Median Win Rate· 2023-06-04
89.77
SOTA
A Unified Framework for Factorizing Distributional Value Functions for Multi-Agent Reinforcement Learning arXiv:2306.02430
SMAConSMAC MMM2_7m2M1M_vs_8m4M1M
Average Score· 2023-06-04
16.5
SOTA
A Unified Framework for Factorizing Distributional Value Functions for Multi-Agent Reinforcement Learning arXiv:2306.02430
SMAConSMAC corridor_2z_vs_24zg
Average Score· 2023-06-04
11.1
SOTA
A Unified Framework for Factorizing Distributional Value Functions for Multi-Agent Reinforcement Learning arXiv:2306.02430
SMAConSMAC corridor_2z_vs_24zg
Median Win Rate· 2023-06-04
41.19
SOTA
A Unified Framework for Factorizing Distributional Value Functions for Multi-Agent Reinforcement Learning arXiv:2306.02430
SMAConSMAC MMM2_7m2M1M_vs_9m3M1M
Average Score· 2023-06-04
19.45
SOTA
A Unified Framework for Factorizing Distributional Value Functions for Multi-Agent Reinforcement Learning arXiv:2306.02430
SMAConSMAC 3s5z_vs_3s6z
Average Score· 2021-02-16
20.94
SOTA
DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning arXiv:2102.07936
SMAConSMAC 3s5z_vs_3s6z
Median Win Rate· 2021-02-16
94.03
best: 100 (ACE)
SOTA
DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning arXiv:2102.07936
SMAConSMAC corridor
Average Score· 2021-02-16
20
SOTA
DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning arXiv:2102.07936
SMAConSMAC corridor
Median Win Rate· 2021-02-16
95.4
best: 100 (ACE)
SOTA
DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning arXiv:2102.07936
SMAConSMAC MMM2
Average Score· 2021-02-16
20.9
SOTA
DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning arXiv:2102.07936
SMAConSMAC MMM2
Median Win Rate· 2021-02-16
97.22
best: 100 (ACE)
SOTA
DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning arXiv:2102.07936
SMAConSMAC 6h_vs_8z
Average Score· 2021-02-16
19.4
SOTA
DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning arXiv:2102.07936
SMAConSMAC 6h_vs_8z
Median Win Rate· 2021-02-16
83.92
best: 93.75 (ACE)
SOTA
DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning arXiv:2102.07936
SMAConSMAC 27m_vs_30m
Average Score· 2021-02-16
19.71
SOTA
DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning arXiv:2102.07936
SMAConSMAC 27m_vs_30m
Median Win Rate· 2021-02-16
91.48
SOTA
DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning arXiv:2102.07936
SMAConSMAC 6h_vs_9z
Median Win Rate· 2023-06-04
0.28
best: 1.14 (QMIX)
A Unified Framework for Factorizing Distributional Value Functions for Multi-Agent Reinforcement Learning arXiv:2306.02430
SMAConSMAC MMM2_7m2M1M_vs_8m4M1M
Median Win Rate· 2023-06-04
56.82
best: 63.35 (DMIX)
A Unified Framework for Factorizing Distributional Value Functions for Multi-Agent Reinforcement Learning arXiv:2306.02430
SMAConSMAC MMM2_7m2M1M_vs_9m3M1M
Median Win Rate· 2023-06-04
90.34
best: 92.33 (DMIX)
A Unified Framework for Factorizing Distributional Value Functions for Multi-Agent Reinforcement Learning arXiv:2306.02430
SMAConSMAC 26m_vs_30m
Average Score· 2023-06-04
18.49
best: 19.17 (DMIX)
A Unified Framework for Factorizing Distributional Value Functions for Multi-Agent Reinforcement Learning arXiv:2306.02430
SMAConSMAC 26m_vs_30m
Median Win Rate· 2023-06-04
67.9
best: 81.82 (DMIX)
A Unified Framework for Factorizing Distributional Value Functions for Multi-Agent Reinforcement Learning arXiv:2306.02430
SMAConDef_Infantry_parallel
Median Win Rate· 2021-02-16
20
best: 100 (QTRAN)
DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning arXiv:2102.07936
SMAConDef_Armored_sequential
Median Win Rate· 2021-02-16
71.9
best: 100 (DRIMA)
DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning arXiv:2102.07936
SMAConDef_Infantry_sequential
Median Win Rate· 2021-02-16
90.6
best: 100 (MADDPG)
DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning arXiv:2102.07936
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)
SMAConOff_Superhard_parallel
Median Win Rate
0

Computer Vision2 results

Edge DetectiononUDED
ODS
0.832
Edge DetectiononBIPED
ODS
0.916