Towards Fairer Sanction Systems: Income-Based Models with Aggregation Functions

This paper presents a novel framework for designing income-based fines that integrate both the severity of the offence and the financial capacity of the offender. The model employs a grid-based interpolation approach, initially using bilinear interpolation and then extending to more expressive aggregation techniques such as the Choquet integral and t-norms.This generalization allows for customizable sanction functions that reflect diverse legal and ethical priorities. Numerical simulations illustrate the impact of different aggregation strategies on fine outcomes.