AR公平性元模型：一种公平性度量的结构化框架
The AR Fairness Metamodel: A Structured Framework for Fairness Measures
- Umeå University（于默奥大学）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
本文提出AR公平性元模型，基于Tiles框架，系统定义和比较多种公平性度量，涵盖离散与连续指标，并探讨群体、个体公平及无嫉妒性关系，提供开源工具支持。
AI中文摘要：
本文提出了AR公平性元模型，这是一个旨在表示、分析和比较不同公平性场景的框架。该元模型考虑了关键要素，如智能体、资源及其属性，并能够系统地定义和比较各种公平性度量。我们提供了涉及离散和连续度量的示例，包括平等、公平、群体公平、个体公平、基尼指数、泰尔指数、Jain公平指数，以及针对澳大利亚儿童保育补贴的详细公平性度量。我们还探讨了群体公平、个体公平和无嫉妒性之间的关系，并辅以形式化证明。在概念建模层面，我们的方法基于Tiles框架，该框架提供了可连接的模块化组件，以捕获各种公平性定义。目标是使基于AR的公平性定义在不同情境下实用且可适应，提供一种清晰的方式来定义、比较和评估它们。Tiles框架的实现可作为开源工具获得，并能在广泛的应用中支持公平性建模和评估。
英文摘要：
This paper presents the AR fairness metamodel, a framework designed to represent, analyze, and compare different fairness scenarios. The metamodel considers key elements, such as agents, resources, and their attributes, and enables the systematic definition and comparison of various fairness measures. We provide examples involving both discrete and continuous measures, including equality, equity, group fairness, individual fairness, the Gini index, the Theil index, Jain's fairness index, and a detailed fairness measure for Australia's Child Care Subsidy. We also explore relationships among group fairness, individual fairness, and envy-freeness, supported by formal proofs. At the conceptual modeling level, our approach builds on the Tiles framework, which offers modular components that can be connected to capture diverse fairness definitions. The goal is to make AR-based fairness definitions practical and adaptable across contexts, providing a clear way to define, compare, and evaluate them. An implementation of the Tiles framework is available as an open-source tool, and can support fairness modeling and evaluation across a wide range of applications.
