Search and Rediscovery
Martino Banchio (Google Research)
Paper joint with Suraj Malladi (Northwestern Kellogg)
Abstract:
We model search in unfamiliar territories, where agents know what can be found but not where to find it. A searcher faces a set of choice arranged by an observable attribute. Each period, she either selects a choice and pays a cost to learn about its quality, or she concludes search to take her best discovery to date. She knows that similar choices have similar qualities and uses this to guide her search. We identify robustly optimal search policies with a simple structure. Search is ordered, perfect recall is never invoked, stopping follows a threshold rule, and the policy at each history depends only on a simple index.