When to stop searching in a highly uncertain world? A theoretical and experimental investigation of “two-way” sequential search tasks

Abstract

When to stop exploring is crucial in contexts where learning to manage time and uncertainty is critical for carrying out successful initiatives (e.g., innovation, personnel recruitment, vaccine discovery). We investigate analytically and experimentally the exploration-exploitation trade-offs in such contexts. A “two-way” sequential search task is proposed, where the classical exploration-exploitation trade-off in sequential decisions with finite-horizon is coupled with a further one about discovering the real value of each alternative. The longer the time spent on a specific alternative, the higher the certainty about its expected value but at the higher cost of an under-exploitation of the best alternative so far explored. People learn better when to stop the more certain the information is. A potential behavioral trap in the exploration of “two-way” search tasks is identified that brings towards local optima. We recommend policies that induce people to reduce the time spent exploring the alternatives.