  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.

Human-Computer Interaction