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This section contains literature about libalf.

Further Reading

For more information about the learning algorithms which are implemented in libalf we recommend the following literature.

  • D. Angluin. Learning Regular Sets from Queries and Counterexamples. Information and Computation, 75(2):87 to 106, 1987.
  • A. W. Biermann and J. Feldman. On the Synthesis of Finite-State Machines from Samples of Their Behavior. IEEE TSE, 21(6):592 to 597, 1972.
  • R.L. Rivest and R.E. Schapire. Inference of finite automata using homing sequences. In Machine Learning: From Theory to Applications, LNCS 661, pages 51 to 73, 1993.
  • B. Bollig, P. Habermehl, C. Kern, and M. Leucker. Angluin-Style Learning of NFA. In IJCAI 2009, pages 1004 to 1009. AAAI Press, 2009.
  • F. Denis, A. Lemay, and A. Terlutte. Learning regular languages using RFSAs. TCS, 313(2):267 to 294, 2004.
  • M. Kearns and U. Vazirani. An Introduction to Computational Learning Theory, 1994.
  • J. Oncina and P. García. Inferring Regular Languages in Polynomial Updated Time. In the 4th Spanish Symposium on Pattern Recognition and Image Analysis, volume 1 of MPAI, pages 49 to 61. World Scientific, 1992.

Latest news

April 9th, 2011

Release of libalf 0.3. Version 0.3 features some new features and the Rivest / Schapire learning algorithm. Please have a look at the Changelog.

March 10th, 2010

Release of libalf 0.2. Version 0.2 now features the Kearns / Vazirani and Biermann's original learning algorithm. Additionally, various bugs are fixed.

October 19th, 2009

libalf website launched. On October 19th, 2009 the libalf team launched the new website.

October 12th, 2009

libalf released. The first beta of the libalf library has been released.

libalf demo

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