析取分隔控制

IF 1.4 2区 数学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING
ALEXANDER VANDENBROUCKE, TOM SCHRIJVERS
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引用次数: 0

摘要

分隔控制是一种强大的编程语言扩展机制,它最近被提出用于Prolog(并在SWI-Prolog中实现)。通过在语言内部操纵程序的控制流,它可以实现强大的功能,例如表,而无需修改Prolog引擎的内部。然而,它目前的表述是不充分的:它没有捕捉到Prolog独特的非确定性性质,允许多种方法来满足一个目标。本文充分利用Prolog的非确定性,为析取定界控制提供了一个新的接口,使程序员不仅可以控制顺序(合取)控制流,还可以控制非确定性控制流。我们提供了一个元解释器,它保守地扩展了带有分隔控制的Prolog,并显示它支持一系列典型的Prolog功能和扩展,现在在库级别:findall, cut,分支和绑定优化,概率编程,…
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Disjunctive Delimited Control
Abstract Delimited control is a powerful mechanism for programming language extension which has been recently proposed for Prolog (and implemented in SWI-Prolog). By manipulating the control flow of a program from inside the language, it enables the implementation of powerful features, such as tabling, without modifying the internals of the Prolog engine. However, its current formulation is inadequate: it does not capture Prolog’s unique non-deterministic nature which allows multiple ways to satisfy a goal. This paper fully embraces Prolog’s non-determinism with a novel interface for disjunctive delimited control, which gives the programmer not only control over the sequential (conjunctive) control flow, but also over the non-deterministic control flow. We provide a meta-interpreter that conservatively extends Prolog with delimited control and show that it enables a range of typical Prolog features and extensions, now at the library level: findall, cut, branch-and-bound optimisation, probabilistic programming, …
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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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