arXiv:2510.16001cs.AI2025-10

提出一种考虑顺序的随机排列集冲突度量方法。

An Order-Sensitive Conflict Measure for Random Permutation Sets

  • 基于置信结构理论,将顺序信息融入焦点集冲突判断。
  • 冲突度量具有层次加权特性,能区分不同程度的矛盾。
  • 适合需要灵活调整权重与截断深度的决策场景。

随机排列集(RPS)是一种用于处理包含顺序信息的不确定性推理的新形式。在依赖顺序的不确定信息融合中,衡量由排列质量函数表示的两段证据之间的冲突仍是一个开放问题。本文从随机有限集(RFS)和达姆斯特-沙弗理论(DST)两个角度分析了RPS中的冲突。从DST视角看,纳入焦点集的顺序信息反映了高排名元素更重要的定性倾向。受此启发并结合对排列的观察,本文定义了一种非重叠型不一致度量,并提出了针对RPS的顺序敏感冲突度量。该方法将RPS冲突重新表述为一种分级的、依赖顺序的概念,而非简单的冲突/非冲突二分。数值例子验证了所提度量的行为与性质。该方法不仅在DST框架内具备内在的顶部加权特性,有效量化了RPS间的冲突,还为决策者提供了选择权重、参数和截断深度的灵活性。

原文摘要 · Abstract (English)

Random permutation set (RPS) is a new formalism for reasoning with uncertainty involving order information. Measuring the conflict between two pieces of evidence represented by permutation mass functions remains an open issue in order-dependent uncertain information fusion. This paper analyzes conflicts in RPS from two different perspectives: random finite set (RFS) and Dempster-Shafer theory (DST). From the DST perspective, the order information incorporated into focal sets reflects a qualitative propensity where higher-ranked elements are more significant. Motivated by this view and observations on permutations, we define a non-overlap-based inconsistency measure for permutations and develop an order-sensitive conflict measure for RPSs. The proposed method reformulates the conflict in RPSs as a graded, order-dependent notion rather than a simple dichotomy of conflict versus non-conflict. Numerical examples are presented to validate the behavior and properties of the proposed conflict measure. The proposed method not only exhibits an inherent top-weightedness property and effectively quantifies conflict between RPSs within the DST framework, but also provides decision-makers with flexibility in selecting weights, parameters, and truncation depths.

不确定性推理置信规则顺序信息

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