Learning while searching for the best alternative

This paper delivers the solution to an optimal search problem where the sea rcher faces more than one search alternative and is learning about the attr activeness of the respective alternatives during the search process. The op timal sampling strategy is characterized by simple reservation prices that determine which of the search alternatives to sample and when to stop searc hing. The reservation price criterion is optimal for a large class of learn ing rules, including Bayesian, nonparametric, and ad-hoc learning rules. Th e considered search problem contains as special cases many earlier contribu tions to the search literature and thereby unifies and generalizes two dire ctions of research search with learning from a single search alternative an d search without learning from several search alternatives. (C) 2001 Academ ic Press.