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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.

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

  • 会议论文

  • 发表日期：

    2025年

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  • Luca Anzilli,
  • Marta Cardin,
  • Silvio Giove

摘要

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.