PIs: Dr. Jonathan Nelson, Dr. Björn Meder, Prof. Dr. Laura Martignon, Dr. Vincenzo Crupi
Involved: Prof. Dr. Katya Tentori
Institutions: Max-Planck-Institut für Bildungsforschung Berlin, Pädagogische Hochschule Ludwigsburg, Universität Turin, Universität Trento

Abstract
This project explores the relationship between fully rational (inductive confirmation and value-of-information) and more boundedly and ecologically rational (heuristic) approaches to information search. Our research combines theoretical, computational, and empirical investigations of alternative models, in different environments. We theoretically analyze alternative inductive confirmation measures (Crupi, Tentori, & Gonzalez, 2007), which quantify the confirmation or disconfirmation that acquired evidence provides for particular hypotheses, from the perspective of models of information search (Nelson, 2005). Our analyses provide novel insights into traditional debates in the philosophy of science, and enable the development of novel models of information search based on confirmation measures. In particular, our work bridges a gap between two classes of models that have not been linked to each other before: confirmation measures, as discussed in epistemology and philosophy of science (Crupi, Chater, & Tentori, 2013; Crupi & Tentori, 2013) and models that quantify the value of information, as discussed in statistics and cognitive science. We use computer simulations to identify and characterize environments in which confirmation-, value-of-information-, and heuristic-based models agree with or contradict each other. These theoretical and computational analyses guide our empirical studies with children (Nelson, Divjak, Gudmundsdottir, Martignon, & Meder, 2014; Martignon & Krauss, 2009) and adults (Meder & Nelson, 2012). The overall scope is to establish a comprehensive theory of human information acquisition and its rational bases.

Project-related Publications
Nelson, J. D., Divjak, B., Gudmundsdottir, G., Martignon, L. F., & Meder, B. (2014). Children's information search is sensitive to environmental probabilities. Cognition, 130, 74-80.
Crupi, V., Chater, N., & Tentori, K. (2013). New axioms for probability and likelihood ratio measures. British Journal for the Philosophy of Science, 64, 189-204.
Meder, B., & Nelson, J. D. (2012). Information search with situation-specific reward functions. Judgment and Decision Making, 7, 119-148.
More publications can be found on this page.

Relation to the SPP1516's second funding period
This project continues during the second funding period. Go to project page...