Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.jcss.2011.12.011
Title: Learnability of automatic classes
Authors: Jain, S. 
Luo, Q.
Stephan, F. 
Keywords: Automatic structures
Inductive inference
Issue Date: 2012
Source: Jain, S., Luo, Q., Stephan, F. (2012). Learnability of automatic classes. Journal of Computer and System Sciences 78 (6) : 1910-1927. ScholarBank@NUS Repository. https://doi.org/10.1016/j.jcss.2011.12.011
Abstract: The present work initiates the study of the learnability of automatic indexable classes which are classes of regular languages of a certain form. Angluin's tell-tale condition characterises when these classes are explanatorily learnable. Therefore, the more interesting question is when learnability holds for learners with complexity bounds, formulated in the automata-theoretic setting. The learners in question work iteratively, in some cases with an additional long-term memory, where the update function of the learner mapping old hypothesis, old memory and current datum to new hypothesis and new memory is automatic. Furthermore, the dependence of the learnability on the indexing is also investigated. This work brings together the fields of inductive inference and automatic structures. © 2012 2012 Elsevier Inc. All rights reserved.
Source Title: Journal of Computer and System Sciences
URI: http://scholarbank.nus.edu.sg/handle/10635/43288
ISSN: 00220000
DOI: 10.1016/j.jcss.2011.12.011
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