@techreport{40a631180de34c55b7a797618893ad61,
title = "Robust sequential search",
abstract = "We study sequential search without priors. Our interest lies in decision rules that are close to being optimal under each prior and after each history. We call these rules dynamically robust. The search literature employs optimal rules based on cuto strategies that are not dynamically robust. We derive dynamically robust rules and show that their performance exceeds 1/2 of the optimum against binary environments and 1/4 of the optimum against all environments. This performance improves substantially with the outside option value, for instance, it exceeds 2/3 of the optimum if the outside option exceeds 1/6 of the highest possible alternative.",
keywords = "Sequential search, Search without priors, Robust control, Competitive ratio, Dynamic consistency",
author = "Karl Schlag and Andriy Zapechelnyuk",
note = "Revised 11 Mar 2019, revised 12 Jul 2019, revised 4 Aug 2020",
year = "2020",
month = aug,
day = "4",
language = "English",
series = "School of Economics and Finance Discussion Paper",
publisher = "University of St Andrews",
number = "1803",
type = "WorkingPaper",
institution = "University of St Andrews",
}