“如果什么?在概率逻辑规划中

IF 1.4 2区 数学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING Theory and Practice of Logic Programming Pub Date : 2023-07-01 DOI:10.1017/s1471068423000133
RAFAEL KIESEL, KILIAN RÜCKSCHLOß, FELIX WEITKÄMPER
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引用次数: 0

摘要

ProbLog程序是一种逻辑程序,它的事实只以特定的概率存在。在本文中,我们通过回答“What if”查询的能力扩展了ProbLog语言。直观地说,ProbLog程序通过根据相互独立的预定义布尔随机变量求解方程组来定义分布。在因果关系理论中,朱迪亚·珀尔为这样的方程组提出了一种反事实推理。基于Pearl的演算,我们提供了一个在ProbLog程序上处理这些反事实查询的程序,以及正确性的证明和完整的实现。使用后者,我们可以深入了解不同参数对推理可扩展性的影响。最后,我们还证明了我们的方法与CP-logic一致,即与带有析取注释的逻辑程序的因果语义一致。
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“What if?” in Probabilistic Logic Programming
Abstract A ProbLog program is a logic program with facts that only hold with a specified probability. In this contribution, we extend this ProbLog language by the ability to answer “What if” queries. Intuitively, a ProbLog program defines a distribution by solving a system of equations in terms of mutually independent predefined Boolean random variables. In the theory of causality, Judea Pearl proposes a counterfactual reasoning for such systems of equations. Based on Pearl’s calculus, we provide a procedure for processing these counterfactual queries on ProbLog programs, together with a proof of correctness and a full implementation. Using the latter, we provide insights into the influence of different parameters on the scalability of inference. Finally, we also show that our approach is consistent with CP-logic, that is with the causal semantics for logic programs with annotated with disjunctions.
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来源期刊
Theory and Practice of Logic Programming
Theory and Practice of Logic Programming 工程技术-计算机:理论方法
CiteScore
4.50
自引率
21.40%
发文量
40
审稿时长
>12 weeks
期刊介绍: Theory and Practice of Logic Programming emphasises both the theory and practice of logic programming. Logic programming applies to all areas of artificial intelligence and computer science and is fundamental to them. Among the topics covered are AI applications that use logic programming, logic programming methodologies, specification, analysis and verification of systems, inductive logic programming, multi-relational data mining, natural language processing, knowledge representation, non-monotonic reasoning, semantic web reasoning, databases, implementations and architectures and constraint logic programming.
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