关于评价投票的数据模拟的注记
A Note on Data Simulations for Voting by Evaluation
摘要：
最近提出了基于评价输入而不是偏好顺序的投票规则，如多数判断，范围投票或批准投票。传统上，投票规则的概率分析假设使用模拟模型来生成偏好数据，如公平文化（IC）或公平匿名文化（IAC）模型。但这些模拟模型并不适用于分析基于评价的投票规则，因为它们生成的是偏好顺序而不是所需的评价。在本文中，我们提出了几个模拟模型产生基于评估的投票输入。这些模型，灵感来自经典的，定义，测试和比较推荐的目的。
英文摘要：
Voting rules based on evaluation inputs rather than preference orders have been recently proposed, like majority judgement, range voting or approval voting. Traditionally, probabilistic analysis of voting rules supposes the use of simulation models to generate preferences data, like the Impartial Culture (IC) or Impartial and Anonymous Culture (IAC) models. But these simulation models are not suitable for the analysis of evaluation-based voting rules as they generate preference orders instead of the needed evaluations. We propose in this paper several simulation models for generating evaluation-based voting inputs. These models, inspired by classical ones, are defined, tested and compared for recommendation purpose.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
