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Learning Linearly-Moded Programs from Entailment

机译:从蕴涵中学习线性调制程序

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摘要

Logic programs with elegant and simple declarative semantics have become very common in many areas of artificial intelligence such as knowledge acquisition, knowledge representation and common sense and legal reasoning. For example, in Human GENOME project, logic programs are used in the analysis of amino acid sequences, protein structure and drug design etc. In this paper, we study exact learning of logic programs from entailment and present a polynomial time algorithm to learn a rich class of logic programs that allow local variables and include many programs from Sterling and Shapiro's book [20] such as add, append, merge, split, delete, insert, member, prefix, suffix, length, quick-sort, merge-sort, insertion-sort, preorder and inorder traversal of binary trees, polynomial recognition, derivatives, sum of a list of natural numbers etc.
机译:具有优雅而简单的声明性语义的逻辑程序已在人工智能的许多领域中变得非常普遍,例如知识获取,知识表示,常识和法律推理。例如,在人类基因组计划中,逻辑程序用于分析氨基酸序列,蛋白质结构和药物设计等。在本文中,我们从必要性出发研究逻辑程序的精确学习,并提出了多项式时间算法来学习丰富的允许局部变量的逻辑程序类,包括Sterling和Shapiro的书[20]中的许多程序,例如添加,附加,合并,拆分,删除,插入,成员,前缀,后缀,长度,快速排序,合并排序,二叉树的插入排序,预排序和有序遍历,多项式识别,导数,自然数列表的总和等。

著录项

  • 来源
  • 会议地点 Singapore(SG);Singapore(SG)
  • 作者单位

    School of Computing and Information Technology Faculty of Information and Communication Technology Griffith University, Brisbane 4111, Australia;

    School of Computing and Information Technology Faculty of Information and Communication Technology Griffith University, Brisbane 4111, Australia;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 自动化系统理论;
  • 关键词

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