- Nobandegani, A. S., & Shultz, R. (2020). A resource-rational, process-level account of the St. Petersburg Paradox. Topics in Cognitive Science, 1–16. pdf - The St. Petersburg paradox is a centuries‐old philosophical puzzle concerning a lottery with infinite expected payoff for which people are only willing to pay a small amount to play. Despite many attempts and several proposals, no generally accepted resolution is yet at hand. In this work, we present the first resource‐rational, process‐level explanation of this paradox, demonstrating that it can be accounted for by a variant of normative expected utility valuation which acknowledges cognitive limitations. We show that our metacognitively rational model, sample‐based expected utility (SbEU), can account for major experimental findings on this paradox. Our resolution is consistent with two empirically well‐supported assumptions: (a) People use only a few samples in probabilistic judgments and decision‐making, and (b) people tend to overestimate the probability of extreme events in their judgment. We frame the St. Petersburg gamble as a risky gamble whose process‐level explanation is consistent with a broader process‐level model of human decision‐making under risk. (An earlier version won Best paper award in Computational Modeling of Higher-level Cognition at the 41st Annual Conference of the Cognitive Science Society, 2019, Montreal. Another version was selected to represent the 2019 Cognitive Science conference at the 2020 sister AAAI conference, NYC.)
- Helfer, P., & Shultz, T. R. (2014). The effects of nutrition labeling on consumer food choice: a psychological experiment and computational model. Annals of the New York Academy of Sciences, 1331(1), 174-185. pdf - Quantitative, single-attribute nutrition labels have greater usability than multiattribute and binary labels, with or without time pressure. A decision-field-theory neural network simulates these psychological results and provides explanatory insights into them.