Please use this identifier to cite or link to this item: https://doi.org/10.1007/978-3-642-34106-9_9
Title: Automatic learning from positive data and negative counterexamples
Authors: Jain, S. 
Kinber, E.
Issue Date: 2012
Source: Jain, S.,Kinber, E. (2012). Automatic learning from positive data and negative counterexamples. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 7568 LNAI : 66-80. ScholarBank@NUS Repository. https://doi.org/10.1007/978-3-642-34106-9_9
Abstract: We introduce and study a model for learning in the limit by finite automata from positive data and negative counterexamples. The focus is on learning classes of languages with a membership problem computable by finite automata (so-called automatic classes). We show that, within the framework of our model, finite automata (automatic learners) can learn all automatic classes when memory of a learner is restricted by the size of the longest datum seen so far. We also study capabilities of automatic learners in our model with other restrictions on the memory and how the choice of negative counterexamples (arbitrary, or least, or the ones whose size is bounded by the longest positive datum seen so far) can impact automatic learnability. © 2012 Springer-Verlag.
Source Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
URI: http://scholarbank.nus.edu.sg/handle/10635/39898
ISBN: 9783642341052
ISSN: 03029743
DOI: 10.1007/978-3-642-34106-9_9
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