A Human-Computer Interface Design for Quantitative Measure of Regret Theory

TL;DR

This paper presents a novel human-computer interface for quantitatively measuring regret theory by capturing natural language preferences, reducing cognitive load, and accounting for biases, leading to more accurate decision-making models.

Contribution

It introduces a graphical HCI design that elicits preferences through natural language responses modeled with fuzzy-set theory, improving measurement accuracy of regret theory.

Findings

Model predicts human choices with high accuracy.

Survey design reduces cognitive workload and bias influence.

Responses modeled effectively with fuzzy-set theory.

Abstract

Regret theory is a theory that describes human decision-making under risk. The key of obtaining a quantitative model of regret theory is to measure the preference in humans' mind when they choose among a set of options. Unlike physical quantities, measuring psychological preference is not procedure invariant, i.e. the readings alter when the methods change. In this work, we alleviate this influence by choosing the procedure compatible with the way that an individual makes a choice. We believe the resulting model is closer to the nature of human decision-making. The preference elicitation process is decomposed into a series of short surveys to reduce cognitive workload and increase response accuracy. To make the questions natural and familiar to the subjects, we follow the insight that humans generate, quantify and communicate preference in natural language. The fuzzy-set theory is hence utilized to model responses from subjects. Based on these ideas, a graphical human-computer interface (HCI) is designed to articulate the information as well as to efficiently collect human responses. The design also accounts for human heuristics and biases, e.g. range effect and anchoring effect, to enhance its reliability. The overall performance of the survey is satisfactory because the measured model shows prediction accuracy equivalent to the revisit-performance of the subjects.