Learning2Reason

  • Daniel Kühlwein
  • Josef Urban
  • Evgeni Tsivtsivadze
  • Herman Geuvers
  • Tom Heskes
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6824)

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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    Tsivtsivadze, E., Urban, J., Geuvers, H., Heskes, T.: Semantic Graph Kernels for Automated Reasoning. In: SIAM Conference on Data Mining (2011)Google Scholar
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    Urban, J., Sutcliffe, G., Pudlák, P.: Malarea SG1-machine learner for automated reasoning with semantic guidance. In: Armando, A., Baumgartner, P., Dowek, G. (eds.) IJCAR 2008. LNCS (LNAI), vol. 5195, pp. 441–456. Springer, Heidelberg (2008)CrossRefGoogle Scholar

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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