Logic-based machine learning

被引：0

作者：

Muggleton, S ^{[1
]}

Marginean, F ^{[1
]}

机构：

[1] Univ York, Dept Comp Sci, York YO1 5DD, N Yorkshire, England

来源：

LOGIC-BASED ARTIFICIAL INTELLIGENCE | 2000年 / 597卷

关键词：

inductive logic programming; machine learning; scientific discovery; protein prediction; learning of natural language;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The last three decades has seen the development of Computational Logic techniques within Artificial Intelligence. This has led to the development of the subject of Logic Programming (LP), which can be viewed as a key part of Logic-Based Artificial Intelligence. The subtopic of LP concerned with Machine Learning is known as "Inductive Logic Programming" (ILP), which again can be broadened to Logic-Based Machine Learning by dropping Horn clause restrictions. ILP has its roots in the ground-breaking research of Cordon Plotkin and Ehud Shapiro. This paper provides a brief survey of the state of ILP applications, theory and techniques.

引用

页码：315 / 330

页数：16

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