We introduce a notion of fairest tie-breaking for voting w.r.t. two widely-accepted fairness criteria: anonymity (all voters being treated equally) and neutrality (all alternatives being treated equally). We proposed a polynomial-time computable fairest tie-breaking mechanism, called most-favorable-permutation (MFP) breaking, for a wide range of decision spaces, including single winners, $k$-committees, $k$-lists, and full rankings. We characterize the semi-random fairness of commonly-studied voting rules with MFP breaking, showing that it is significantly better than existing tie-breaking mechanisms, including the commonly-used lexicographic and fixed-agent mechanisms.

翻译：我们引入了两种被广泛接受的公平性标准 — — 匿名(所有选民都得到平等对待)和中立(所有备选方案都得到平等对待 ) 。 我们提出一个公平性最公平性打破机制,称为最优惠-更替(MFP)打破机制(MFP ), 用于一系列广泛的决策空间,包括单一赢家、美元委员会、美元名单和正式排名。 我们将共同研究的投票规则的半随机公平性与MFP的打破定性为“半随机性 ”, 表明它比现有的断裂性机制(包括常用的词汇和固定代理机制)要好得多。