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.
翻译:最近提出了基于评价投入而不是偏好命令的投票规则,如多数人判断、范围投票或批准投票等。传统上,对投票规则的概率分析假定使用模拟模型来生成偏好数据,如中立文化(IC)或公正和匿名文化(IAC)模型。但这些模拟模型不适合分析基于评价的投票规则,因为它们产生偏好命令而不是所需的评价。我们在本文件中提出了若干模拟模型来生成基于评价的投票投入。这些模型受传统模式的启发,为建议目的加以界定、测试和比较。