String Extension Learning

被引：0
作者：
Heinz, Jeffrey [1 ]
机构：
[1] Univ Delaware, Newark, DE 19716 USA
来源：
ACL 2010: 48TH ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS | 2010年
关键词：
LANGUAGES; IDENTIFICATION; FAMILIES; WORD;
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：
This paper provides a unified, learning-theoretic analysis of several learnable classes of languages discussed previously in the literature. The analysis shows that for these classes an incremental, globally consistent, locally conservative, set-driven learner always exists. Additionally, the analysis provides a recipe for constructing new learnable classes. Potential applications include learnable models for aspects of natural language and cognition.
引用
收藏
页码：897 / 906
页数：10
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