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CGE: A sequential learning algorithm for mealy automata
KTH, School of Computer Science and Communication (CSC), Theoretical Computer Science, TCS.ORCID iD: 0000-0002-9706-5008
2010 (English)In: Grammatical Inference: Theoretical Results and Applications 10th International Colloquium, ICGI 2010, Valencia, Spain, September 13-16, 2010. Proceedings / [ed] José M. Sempere and Pedro García, 2010, 148-162 p.Conference paper, Published paper (Refereed)
Abstract [en]

We introduce a new algorithm for sequential learning of Mealy automata by congruence generator extension (CGE). Our approach makes use of techniques from term rewriting theory and universal algebra for compactly representing and manipulating automata using finite congruence generator sets represented as string rewriting systems (SRS). We prove that the CGE algorithm correctly learns in the limit.

Place, publisher, year, edition, pages
2010. 148-162 p.
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 6339
Keyword [en]
Generator sets, Sequential learning, Sequential learning algorithm, String rewriting, Term rewriting, Universal algebra
National Category
Computer and Information Science
Identifiers
URN: urn:nbn:se:kth:diva-62889DOI: 10.1007/978-3-642-15488-1_13ISI: 000312462500013Scopus ID: 2-s2.0-78149252077ISBN: 978-364215487-4 (print)OAI: oai:DiVA.org:kth-62889DiVA: diva2:481294
Conference
10th International Colloquium on Grammatical Inference, ICGI 2010; Valencia; 13 September 2010 through 16 September 2010
Note

QC 20120124

Available from: 2012-01-20 Created: 2012-01-20 Last updated: 2013-12-19Bibliographically approved

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Meinke, Karl

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
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  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
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