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ResearchFormerly WizWand

Sequential Optimal Experimental Design on Location Finding (LF) (test)

4.79sPCERandom
4.46886.63698.80510.9731Dec 28, 2025
Updated 8mo ago

Evaluation results

MethodLinks
RandomEvaluation Horizon (T)=10, Number of Dimensions (K)=2, Number of Contrastive Samples (L)=5*10^52025.124.79
RandomEvaluation Horizon (T)=30, Number of Dimensions (K)=1, Number of Contrastive Samples (L)=10^62025.125.17
SG-BOEDEvaluation Horizon (T)=30, Number of Dimensions (K)=1, Number of Contrastive Samples (L)=10^62025.125.25
SG-BOEDEvaluation Horizon (T)=10, Number of Dimensions (K)=2, Number of Contrastive Samples (L)=5*10^52025.125.55
JADAITraining Horizon (u_t)=u10, Evaluation Horizon (T)=10, Number of Dimensions (K)=2, Number of Contrastive Samples (L)=5*10^52025.126.47
JADAITraining Horizon (u_t)=u20, Evaluation Horizon (T)=10, Number of Dimensions (K)=2, Number of Contrastive Samples (L)=5*10^52025.126.71
JADAITraining Horizon (u_t)=u30, Evaluation Horizon (T)=10, Number of Dimensions (K)=2, Number of Contrastive Samples (L)=5*10^52025.126.74
RandomEvaluation Horizon (T)=20, Number of Dimensions (K)=2, Number of Contrastive Samples (L)=5*10^52025.127
DADEvaluation Horizon (T)=30, Number of Dimensions (K)=1, Number of Contrastive Samples (L)=10^62025.127.33
SG-BOEDEvaluation Horizon (T)=20, Number of Dimensions (K)=2, Number of Contrastive Samples (L)=5*10^52025.127.7
RL-BOEDEvaluation Horizon (T)=30, Number of Dimensions (K)=1, Number of Contrastive Samples (L)=10^62025.127.7
iDADEvaluation Horizon (T)=10, Number of Dimensions (K)=2, Number of Contrastive Samples (L)=5*10^52025.127.75
DADEvaluation Horizon (T)=10, Number of Dimensions (K)=2, Number of Contrastive Samples (L)=5*10^52025.127.97
RandomEvaluation Horizon (T)=30, Number of Dimensions (K)=2, Number of Contrastive Samples (L)=10^62025.128.3
SG-BOEDEvaluation Horizon (T)=30, Number of Dimensions (K)=2, Number of Contrastive Samples (L)=10^62025.128.84
ALINEEvaluation Horizon (T)=30, Number of Dimensions (K)=1, Number of Contrastive Samples (L)=10^62025.128.91
JADAITraining Horizon (u_t)=u30, Evaluation Horizon (T)=30, Number of Dimensions (K)=1, Number of Contrastive Samples (L)=10^62025.129.62
iDADEvaluation Horizon (T)=20, Number of Dimensions (K)=2, Number of Contrastive Samples (L)=5*10^52025.1210.08
DADEvaluation Horizon (T)=20, Number of Dimensions (K)=2, Number of Contrastive Samples (L)=5*10^52025.1210.42
JADAITraining Horizon (u_t)=u20, Evaluation Horizon (T)=20, Number of Dimensions (K)=2, Number of Contrastive Samples (L)=5*10^52025.1210.48
JADAITraining Horizon (u_t)=u30, Evaluation Horizon (T)=20, Number of Dimensions (K)=2, Number of Contrastive Samples (L)=5*10^52025.1210.9
DADEvaluation Horizon (T)=30, Number of Dimensions (K)=2, Number of Contrastive Samples (L)=10^62025.1210.97
RL-BOEDEvaluation Horizon (T)=30, Number of Dimensions (K)=2, Number of Contrastive Samples (L)=10^62025.1211.73
RL-sCEEEvaluation Horizon (T)=30, Number of Dimensions (K)=2, Number of Contrastive Samples (L)=10^62025.1212.31
JADAITraining Horizon (u_t)=u30, Evaluation Horizon (T)=30, Number of Dimensions (K)=2, Number of Contrastive Samples (L)=10^62025.1212.82