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

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