Extensions to the Relational Paths Based Learning Approach RPBL

被引：3
|
作者：
Gao, Zhiqiang [1 ]
Zhang, Zhizheng [1 ]
Huang, Zhisheng [2 ]
机构：
[1] Southeast Univ, Inst Comp Sci & Engn, Nanjing, Peoples R China
[2] Vrije Univ Amsterdam, Dept Comp Sci, Vrije, Netherlands
来源：
2009 FIRST ASIAN CONFERENCE ON INTELLIGENT INFORMATION AND DATABASE SYSTEMS | 2009年
基金：
美国国家科学基金会;
关键词：
D O I：
10.1109/ACIIDS.2009.40
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper we extend RPBL, a Relational Paths Based Learning approach for first order theories in three directions. We apply domain theories to expand structured instance space, learn recursive theories by an example of learningmember relationship of lists, and analyze the performance as well as time complexity theoretically. In addition, we give the details of our experimental results.
引用
收藏
页码：214 / +
页数：2
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