首页> 外文会议>Machine learning >Theory-Guided Induction of Logic Programs by Inference of Regular Languages
【24h】

Theory-Guided Induction of Logic Programs by Inference of Regular Languages

机译:通过常规语言推理对逻辑程序进行理论指导的归纳

获取原文
获取原文并翻译 | 示例

摘要

Previous resolution-based approaches to theory-guided induction of logic programs produce hypotheses in the form of a set of resolvents of a theory, where the resolvents represent allowed sequences of resolution steps for the initial theory. There are, however, many characterizations of allowed sequences of resolution steps that cannot be expressed by a set of resolvents. One approach to this problem is presented, the system merlin, which is based on an earlier technique for learning finite-state automata that represent allowed sequences of resolution steps. MERLIN extends the previous technique in three ways: ⅰ) negative examples are considered in addition to positive examples, ⅱ) a new strategy for performing generalization is used, and ⅲ) a technique for converting the learned automaton to a logic program is included. Results from experiments are presented in which merlin outperforms both a system using the old strategy for performing generalization, and a traditional covering technique. The latter result can be explained by the limited expressiveness of hypotheses produced by covering and also by the fact that covering needs to produce the correct base clauses for a recursive definition before producing the recursive clauses. MERLIN on the other hand does not require that particular examples of the base cases are given, since both base clauses and recursive clauses can be inferred from a single example.
机译:以前基于分辨率的方法以逻辑为指导的逻辑程序归纳方法以一组理论的分解体的形式产生假设,其中,分解体表示初始理论的允许的分解步骤序列。但是,解析步骤的允许序列有许多特征,而这些特征不能由一组解析子表示。提出了解决该问题的一种方法,系统merlin,它基于一种用于学习有限状态自动机的较早技术,该有限状态自动机代表了允许的解决步骤序列。 MERLIN通过三种方式扩展了先前的技术:ⅰ)除了正面示例外,还考虑了负面示例;ⅱ)使用了一种执行通用化的新策略;ⅲ)包括了将学习到的自动机转换为逻辑程序的技术。给出了实验结果,其中merlin优于使用旧的执行概括策略的系统和传统的覆盖技术。后一种结果可以通过覆盖产生的假设的有限表达性来解释,也可以通过以下事实来解释:覆盖需要在产生递归子句之前为递归定义产生正确的基本子句。另一方面,MERLIN不需要给出基本案例的特定示例,因为可以从单个示例中推断出基本子句和递归子句。

著录项

  • 来源
    《Machine learning》|1996年|46-53|共8页
  • 会议地点 Bari(IT);Bari(IT)
  • 作者

    Henrik Bostroem;

  • 作者单位

    Dept. of Computer and Systems Sciences Stockholm University Electrum 230, 164 40 Kista, Sweden;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 计算机的应用;
  • 关键词

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号