2021/05/31 by Henrique de Oliveira, de Oliveira, Henrique, Yuhta Ishii +2
Computer Science · Decision Sciences · #Auction Theory and Applications #FOS: Economics and business #Mobile Crowdsensing and Crowdsourcing #Optimization and Search Problems #Theoretical Economics (econ.TH)
paper · pdf · doi:10.48550/arxiv.2106.00088
openalex publication_date 2021/05/31 · openalex created_date 2021/06/22 · openalex updated_date 2026/07/28
An agent makes decisions based on multiple sources of information. In isolation, each source is well understood, but their correlation is unknown. We study the agent's robustly optimal strategies -- those that give the best possible guaranteed payoff, even under the worst possible correlation. With two states and two actions, we show that a robustly optimal strategy uses a single information source, ignoring all others. In general decision problems, robustly optimal strategies combine multiple sources of information, but the number of information sources that are needed has a bound that only depends on the decision problem. These findings provide a new rationale for why information is ignored.