Models of information search: A theoretical and empirical synthesis

• Applicants: Dr. Vincenzo Crupi, Ph.D.; Professorin Dr. Laura Martignon; Professor Dr. Björn Meder; Dr. Jonathan Nelson, Ph.D.
• Subject Area: General, Cognitive and Mathematical Psychology
• Term: from 2011 to 2019
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 201370582

Searching for relevant information is central to cognition and decision making. A doctor cannot conduct every available medical test when diagnosing a patient. A scientist cannot conduct all potentially relevant experiments. How can we quantify the usefulness of different questions (tests, experiments) and determine which question-selection strategies are best, given a particular task? Which strategies do people use to select questions, given their goals and beliefs about the structure of the environment? Philosophers, psychologists, and statisticians have all been working in these areas, often without awareness of related research in neighboring disciplines. Our project addresses these issues by connecting three classes of models that are closely related theoretically, but that have seldom been considered together: i) probabilistic confirmation measures, as discussed in epistemology and philosophy of science; ii) value-of-information models, from statistics; and iii) boundedly rational heuristic models, from psychology. Probabilistic confirmation measures quantify the amount of support that an obtained datum (such as a medical test result) provides for a particular hypothesis (i.e., that the patient has a particular disease). Value-of-information models, like information gain or probability gain, quantify the overall usefulness of a test result, or the expected usefulness of an experiment, over all considered hypotheses. Heuristic models for question selection specify how a particular test is chosen, but may not attempt to precisely quantify each available test's value. We will use diverse methodologies including mathematical analyses, computer simulations, and behavioral experiments to explore how these areas are related. We will show how confirmation measures and value-of-information models arise from a unified mathematical framework, and how a number of heuristic models arise as special cases of value-of-information models. We will focus on the implications of using different methods to aggregate confirmation into the value of information. Computer simulations will investigate the behavior of many heuristic and value-of-information strategies, providing an integrative perspective on how different strategies relate in different environments. Behavioral experiments will identify which strategies best describe children and adults' choices of questions to ask. Educational studies will test which sequential-search games can most effectively develop children's intuitions about probability and information. Our overarching goal is to bring confirmation and information together in a unified framework that can guide philosophical and psychological research, while contributing to a psychologically and normatively grounded theory of information acquisition.

• DFG Programme: Priority Programmes
• Subproject of: SPP 1516: New Frameworks of Rationality
• International Connection: Italy, USA
• Participating Persons: Dr. Matt Jones; Professorin Dr. Katya Tentori, Ph.D.