Adaptive stochastic search

Abstract

We characterize Simon's (1955) search and satisficing model with an adaptive threshold and random search (SM-AT). The decision maker (DM) consistent with the SM-AT is endowed with a utility function, a random search distribution, and a deterministic but menu-dependent threshold. On any given trial, the DM searches the menu and stops whenever she finds an item with a utility level that is above the threshold. This simple choice procedure accommodates the well-known compromise and attraction effects. The SM-AT is more general than the random utility model and allows for systematic departures from regularity. Its characterization lets us differentiate adaptive satisficing behavior from random preference maximization in a (limited) standard stochastic choice data set.