系统预测器:答案集语义下逻辑程序的接地大小估计器

IF 1.4 2区数学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING

Theory and Practice of Logic Programming Pub Date : 2023-06-22 DOI:10.1017/s1471068423000078

DANIEL BRESNAHAN, NICHOLAS HIPPEN, YULIYA LIERLER

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引用次数: 0

摘要

摘要答案集编程是一种面向复杂组合搜索问题的声明式逻辑编程范式。虽然不同的逻辑程序可以编码相同的问题，但它们的性能可能差别很大。要确定哪个版本的程序性能最好并不总是容易的。我们提出了系统预测器(及其算法后端)，用于估计程序的接地大小，这是一个可以影响系统处理程序性能的度量。我们评估了预测器的影响，当它被用作由答案集编程重写工具投影仪和lpopt产生的重写指南时。结果证明了这种方法的潜力。

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System Predictor: Grounding Size Estimator for Logic Programs under Answer Set Semantics

Abstract Answer set programming is a declarative logic programming paradigm geared towards solving difficult combinatorial search problems. While different logic programs can encode the same problem, their performance may vary significantly. It is not always easy to identify which version of the program performs the best. We present the system predictor (and its algorithmic backend) for estimating the grounding size of programs, a metric that can influence a performance of a system processing a program. We evaluate the impact of predictor when used as a guide for rewritings produced by the answer set programming rewriting tools projector and lpopt . The results demonstrate potential to this approach.

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来源期刊

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

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.