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ResearchFormerly WizWand

Time series prediction on Logistic

0.1883Average RMSENash
0.1209420.5755431.0301451.484747May 6, 2026
Updated 6mo ago

Evaluation results

MethodLinks
NashNumber of agents=5002026.050.1883
NashNumber of agents=1002026.050.19
NashNumber of agents=252026.050.1902
NashOptimization Strategy=Decentralized (Nash), Number of agents=25, Model Architecture=RFN2026.050.1973
NashOptimization Strategy=Decentralized (Nash), Number of agents=100, Model Architecture=RFN2026.050.1976
NashOptimization Strategy=Decentralized (Nash), Number of agents=500, Model Architecture=RFN2026.050.1977
GreedyOptimization Strategy=Greedy, Number of agents=500, Model Architecture=RFN2026.050.2381
GreedyNumber of agents=1002026.050.2431
GreedyOptimization Strategy=Greedy, Number of agents=100, Model Architecture=RFN2026.050.2505
GreedyOptimization Strategy=Greedy, Number of agents=25, Model Architecture=RFN2026.050.2524
GreedyNumber of agents=5002026.050.2556
GreedyNumber of agents=252026.050.2587
NashModel Type=RFN, Agent Pool Size=1002026.050.3457
NashModel Type=RFN, Agent Pool Size=5002026.050.402
NashModel Type=ESN, Agent Pool Size=1002026.050.4423
GreedyModel Type=ESN, Agent Pool Size=5002026.050.4568
NashModel Type=ESN, Agent Pool Size=5002026.050.5578
GreedyModel Type=ESN, Agent Pool Size=1002026.050.7051
GreedyModel Type=RFN, Agent Pool Size=1002026.051.3444
GreedyModel Type=RFN, Agent Pool Size=5002026.051.872