LANGUAGE-LEARNING WITHOUT OVERGENERALIZATION

Authors
Citation
S. Kapur et G. Bilardi, LANGUAGE-LEARNING WITHOUT OVERGENERALIZATION, Theoretical computer science, 141(1-2), 1995, pp. 151-162
Citations number
11
Categorie Soggetti
Computer Sciences","Computer Science Theory & Methods
ISSN journal
03043975
Volume
141
Issue
1-2
Year of publication
1995
Pages
151 - 162
Database
ISI
SICI code
0304-3975(1995)141:1-2<151:LWO>2.0.ZU;2-5
Abstract
Language learnability is investigated in the Gold paradigm of inductiv e inference from positive data. Angluin gave a characterization of lea rnable families in this framework. Here, learnability of families of r ecursive languages is studied when the learner obeys certain natural c onstraints. Exactly learnable families are characterized for prudent l earners with the following types of constraints: (0) conservative, (1) conservative and consistent, (2) conservative and responsive, and (3) conservative, consistent and responsive. The class of learnable famil ies is shown to strictly increase going from (3) to (2) and from (2) t o (1), while it stays the same going from (1) to (0). It is also shown that, when exactness is not required, prudence, consistency and respo nsiveness, even together, do not restrict the power of conservative le arners.