The Sub-proportionality of Subjective Probability Weighting in Poker
by William Clark
Abstract
This study uses Texas Hold’em poker to investigate decision making under uncertainty and the concept of probability weighting, where individuals may overvalue or undervalue uncertain outcomes. I conduct an experiment to assess Cumulative Prospect Theory’s relevance to subjective probabilities in poker by simplifying the game to compare complex and simple gamble evaluations. The research aims to understand how risk preferences and probability estimation without complete information are influenced by individuals’ poker experience and framing effects. We find that deviations from what theory predicts in the subjective-probability Poker frame can be explained well by the framing effects made in the decision maker’s editing phase. By examining the difference in the predictive power of decision making models in explicit vs subjective probability gambles, the study seeks to improve comprehension of cognitive processes in navigating uncertainty.
Professor Philipp Sadowski, Faculty Advisor
Professor Grace Kim, Faculty Advisor
JEL Codes: C91, D80, D91
A computational model of food choice: Utility optimization through external cuing and heuristic search
By Lucie Yang
The field of economics tends to view decision-making through a lens of assumed rationality and utility maximization. Unfortunately, choices in reality tend to be more complicated than perfect conscious value assignment. One such type of decision-making is food choice, which incorporates not only many inherent values (health, taste, price, energy), but also exists in a world of many external influences (marketing, social pressure). The details of the space in which choices are made can be highly influential, disrupting the typical top-down attentional decision-making assumed with a homo economicus. This paper seeks to utilize a behavioral experiment, eye-tracking, and a novel computational model (the drift diffusion model) in an effort to explore how humans make food decisions. The drift diffusion model links the metrics, reaction time, gaze fixations, and eye movement path length and frequency to the probability of subsequently choosing each item. The model takes into account not only the intrinsic attractiveness of each item, but also the context surrounding them, creating group distributions as well as individual distributions for parameters of the decision process. This paper aims to look at various aspects of food decisions: how do personal internal states, visual salience, and external cues effect how one weights the multiple value characteristics of food.
Advisors: Kent Kimbrough, Philip Sadowski, Scott Huettel, Jonathan Winkle | JEL Codes: D8, D80, D87 | Tagged: Decision-Making, Drift Diffusion Model, Food Consumption, Neuroeconomics
