Tournaments are widely used models to represent pairwise dominance between candidates, alternatives, or teams. We study the problem of providing certified explanations for why a candidate appears among the winners under various tournament rules. To this end, we identify minimal supports, minimal sub-tournaments in which the candidate is guaranteed to win regardless of how the rest of the tournament is completed (that is, the candidate is a necessary winner of the sub-tournament). This notion corresponds to an abductive explanation for the question,"Why does the winner win the tournament?", a central concept in formal explainable AI. We focus on common tournament solutions: the top cycle, the uncovered set, the Copeland rule, the Borda rule, the maximin rule, and the weighted uncovered set. For each rule we determine the size of the smallest minimal supports, and we present polynomial-time algorithms to compute them for all solutions except for the weighted uncovered set, for which the problem is NP-complete. Finally, we show how minimal supports can serve to produce compact, certified, and intuitive explanations for tournament solutions.
翻译:锦标赛是广泛用于表示候选者、备选方案或团队之间两两支配关系的模型。我们研究如何为不同锦标赛规则下某候选者成为获胜者提供可验证的解释。为此,我们提出最小支撑集的概念——即保证该候选者无论锦标赛其余部分如何完成都能获胜的最小锦标赛子集(即该候选者是该子锦标赛的必要获胜者)。这一概念对应于对"获胜者为何赢得锦标赛?"这一问题的溯因解释,是形式化可解释人工智能的核心概念。我们聚焦于常见锦标赛解:顶层循环、无覆盖集、科普兰规则、博尔达规则、极大极小规则及加权无覆盖集。针对每种规则,我们确定了最小支撑集的最小规模,并提出了多项式时间算法以计算除加权无覆盖集外的所有解——该问题对于加权无覆盖集是NP完全的。最后,我们展示了如何利用最小支撑集为锦标赛解生成紧凑、可验证且直观的解释。