Autore: Adam, Klaus
Titolo: Learning while searching for thè best alternative
Periodico: European University Institute of Badia Fiesolana (Fi). Department of Economics - Working papers
Anno: 1999 - Fascicolo: 4 - Pagina iniziale: 1 - Pagina finale: 42

This paper delivers thè solution to an optimal search problem with learning where thè searcher has distinguishable search op-portunities. The optimal sampling strategy is characterized by simple reservation prices that determine which of thè search al-ternatives to sample and when to stop search. The reservation price criterion is optimal for a large class of learning rules having thè sc-called falling reservation price property, including Bayesian, non-parametric and ad-hoc learning rules. The considered search problem contains as special cases many earlier contributions to thè search literature and thereby unifies and generalizes two di-rections of research: search with learning from identical search al-ternatives and search without learning from distinguishable search alternatives.


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