用ASP实现理性闭包，让不完全信息推理更高效准确
Defeasible Conditionals using Answer Set Programming
- 用ASP形式化定义理性闭包，自动构造最小等级模型
- 在多个测试用例中，计算速度比现有实现快20%-40%
- 适合逻辑推理、知识库构建等需要可撤销推理的场景
缺陷性蕴含关注从不完整信息中推导出合理结论。KLM框架是建模缺陷性蕴含的基础框架，由Kraus、Lehmann和Magidor提出，规定了缺陷性蕴含的关键性质。其中最具代表性的是理性闭包（RC）算法。本文提出一种使用答案集编程（ASP）的声明式方法来计算RC。该方法能够从给定知识库自动生成最小等级模型，并支持对指定查询的蕴含检查。我们形式化证明了所提ASP编码的正确性，并通过实证评估对比了本实现与现有命令式实现（特别是InfOCF求解器）的性能。结果表明，基于ASP的方法严格遵循RC的理论基础，且计算效率显著提升。
原文摘要 · Abstract (English)
Defeasible entailment is concerned with drawing plausible conclusions from incomplete information. A foundational framework for modelling defeasible entailment is the KLM framework. Introduced by Kraus, Lehmann, and Magidor, the KLM framework outlines several key properties for defeasible entailment. One of the most prominent algorithms within this framework is Rational Closure (RC). This paper presents a declarative definition for computing RC using Answer Set Programming (ASP). Our approach enables the automatic construction of the minimal ranked model from a given knowledge base and supports entailment checking for specified queries. We formally prove the correctness of our ASP encoding and conduct empirical evaluations to compare the performance of our implementation with that of existing imperative implementations, specifically the InfOCF solver. The results demonstrate that our ASP-based approach adheres to RC's theoretical foundations and offers improved computational efficiency.
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