Abstract
A MAT learning algorithm is presented that infers the universal automaton (UA) for a regular target language, using a polynomial number of queries with respect to that automaton. The UA is one of several canonical characterizations for regular languages. Our learner is based on the concept of an observation table, which seems to be particularly fitting for this computational model, and the necessary notions and definitions are adapted from the literature to the case of UA.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Álvarez, G.I., Victoria, J.H., Bravo, E., García, P.: A Non-Deterministic Grammar Inference Algorithm Applied to the Cleavage Site Prediction Problem in Bioinformatics. In: Sempere, García (eds.) [12], pp. 267–270
Angluin, D.: Learning regular sets from queries and counterexamples. Information and Computation 75, 87–106 (1987)
Bollig, B., Habermehl, P., Kern, C., Leucker, M.: Angluin-style learning of NFA. In: Boutilier, C. (ed.) Proceedings of the 21st International Joint Conference on Artificial Intelligence, IJCAI, pp. 1004–1009 (2009)
Bollig, B., Katoen, J.-P., Kern, C., Leucker, M., Neider, D., Piegdon, D.R.: libalf: The Automata Learning Framework. In: Touili, T., Cook, B., Jackson, P. (eds.) CAV 2010. LNCS, vol. 6174, pp. 360–364. Springer, Heidelberg (2010)
Case, J., Jain, S., Ong, Y.S., Semukhin, P., Stephan, F.: Automatic Learners with Feedback Queries. In: Löwe, B., Normann, D., Soskov, I., Soskova, A. (eds.) CiE 2011. LNCS, vol. 6735, pp. 31–40. Springer, Heidelberg (2011)
Clark, A.: Distributional Learning of Some Context-Free Languages with a Minimally Adequate Teacher. In: Sempere, García (eds.) [12], pp. 24–37
Clark, A.: Learning Context-Free Grammars with the Syntactic Concept Lattice. In: Sempere, García (eds.) [12], pp. 38–51
Courcelle, B., Niwinski, D., Podelski, A.: A geometrical view of the determinization and minimization of finite-state automata. Mathematical Systems Theory 24(2), 117–146 (1991)
García, P., Vázquez de Parga, M., Álvarez, G.I., Ruiz, J.: Universal automata and NFA learning. Theoretical Computer Science 407(1-3), 192–202 (2008)
Lombardy, S., Sakarovitch, J.: The universal automaton. In: Grädel, E., Flum, J., Thomas, W. (eds.) Logic and Automata: History and Perspectives, pp. 457–504. Amsterdam University Press (2008)
Merten, M., Steffen, B., Howar, F., Margaria, T.: Next Generation LearnLib. In: Abdulla, P.A., Leino, K.R.M. (eds.) TACAS 2011. LNCS, vol. 6605, pp. 220–223. Springer, Heidelberg (2011)
Sempere, J.M., García, P. (eds.): ICGI 2010. LNCS, vol. 6339. Springer, Heidelberg (2010)
Stephan, F., Ventsov, Y.: Learning algebraic structures from text. Theoretical Computer Science 268(2), 221–273 (2001)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Björklund, J., Fernau, H., Kasprzik, A. (2013). MAT Learning of Universal Automata. In: Dediu, AH., Martín-Vide, C., Truthe, B. (eds) Language and Automata Theory and Applications. LATA 2013. Lecture Notes in Computer Science, vol 7810. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37064-9_14
Download citation
DOI: https://doi.org/10.1007/978-3-642-37064-9_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-37063-2
Online ISBN: 978-3-642-37064-9
eBook Packages: Computer ScienceComputer Science (R0)