Learning while searching for the best alternative
成果类型：
Article
署名作者：
Adam, K
署名单位：
European University Institute
刊物名称：
JOURNAL OF ECONOMIC THEORY
ISSN/ISSBN：
0022-0531
DOI：
10.1006/jeth.2000.2723
发表日期：
2001
页码：
252-280
关键词：
摘要：
This paper delivers the solution to an optimal search problem where the searcher faces more than one search alternative and is learning about the attractiveness of the respective alternatives during the search process. The optimal sampling strategy is characterized by simple reservation prices that determine which of the search alternatives to sample and when to stop searching. The reservation price criterion is optimal for a large class of learning rules, including Bayesian, nonparametric, and ad-hoc learning rules. The considered search problem contains as special cases many earlier contributions to the search literature and thereby unifies and generalizes two directions of research search with learning from a single search alternative and search without learning from several search alternatives. (C) 2001 Academic Press.