Learning2Reason

  • Daniel Kühlwein
  • Josef Urban
  • Evgeni Tsivtsivadze
  • Herman Geuvers
  • Tom Heskes
Conference paper

DOI: 10.1007/978-3-642-22673-1_27

Part of the Lecture Notes in Computer Science book series (LNCS, volume 6824)
Cite this paper as:
Kühlwein D., Urban J., Tsivtsivadze E., Geuvers H., Heskes T. (2011) Learning2Reason. In: Davenport J.H., Farmer W.M., Urban J., Rabe F. (eds) Intelligent Computer Mathematics. CICM 2011. Lecture Notes in Computer Science, vol 6824. Springer, Berlin, Heidelberg

Abstract

In recent years, large corpora of formally expressed knowledge have become available in the fields of formal mathematics, software verification, and real-world ontologies. The Learning2Reason project aims to develop novel machine learning methods for computer-assisted reasoning on such corpora. Our global research goals are to provide good methods for selecting relevant knowledge from large formal knowledge bases, and to combine them with automated reasoning methods.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Daniel Kühlwein
    • 1
  • Josef Urban
    • 1
  • Evgeni Tsivtsivadze
    • 1
  • Herman Geuvers
    • 1
  • Tom Heskes
    • 1
  1. 1.Institute for Computing and Information SciencesRadboud University NijmegenThe Netherlands

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