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Applying case-based reasoning to automated deduction

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Book cover Case-Based Reasoning Research and Development (ICCBR 1997)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1266))

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Abstract

The use of CBR has been very profitable for many areas of artificial intelligence. Applying CBR to automated deduction, however, is a very intricate problem. The premise “small changes of a problem cause small changes of its solution” is definitely not satisfied by automated deduction. Therefore, case adaptation by means of symbolic proof transformation techniques is very limited.

In view of the fact that automated deduction essentially is a search problem, we propose to utilize case adaptation for selecting and configuring a search-guiding heuristic based on known cases. This also allows us to elegantly integrate methods for learning search-guiding heuristics which can significantly improve performance. The evaluation step of CBR corresponds to an attempt of the theorem prover at hand to solve a problem employing the heuristic provided by case adaptation. Experimental studies demonstrated that this approach is viable and actually produces promising results.

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Author information

Authors and Affiliations

  1. Fakultät für Informatik, TU München, 80290, München, Germany

    Marc Fuchs

  2. Center for Learning Systems and Applications (LSA), Fachbereich Informatik, Universität Kaiserslautern, 67663, Kaiserslautern, Germany

    Matthias Fuchs

Authors
  1. Marc Fuchs
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  2. Matthias Fuchs
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David B. Leake Enric Plaza

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© 1997 Springer-Verlag Berlin Heidelberg

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Fuchs, M., Fuchs, M. (1997). Applying case-based reasoning to automated deduction. In: Leake, D.B., Plaza, E. (eds) Case-Based Reasoning Research and Development. ICCBR 1997. Lecture Notes in Computer Science, vol 1266. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-63233-6_475

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  • DOI: https://doi.org/10.1007/3-540-63233-6_475

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-63233-7

  • Online ISBN: 978-3-540-69238-6

  • eBook Packages: Springer Book Archive

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