English

Lock in Feedback in Sequential Experiments

Machine Learning 2016-01-13 v3

Abstract

We often encounter situations in which an experimenter wants to find, by sequential experimentation, xmax=argmaxxf(x)x_{max} = \arg\max_{x} f(x), where f(x)f(x) is a (possibly unknown) function of a well controllable variable xx. Taking inspiration from physics and engineering, we have designed a new method to address this problem. In this paper, we first introduce the method in continuous time, and then present two algorithms for use in sequential experiments. Through a series of simulation studies, we show that the method is effective for finding maxima of unknown functions by experimentation, even when the maximum of the functions drifts or when the signal to noise ratio is low.

Cite

@article{arxiv.1502.00598,
  title  = {Lock in Feedback in Sequential Experiments},
  author = {Maurits Kaptein and Davide Iannuzzi},
  journal= {arXiv preprint arXiv:1502.00598},
  year   = {2016}
}

Comments

20 Pages, 7 Figures

R2 v1 2026-06-22T08:19:30.560Z