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Applying Preference Biases to Conjunctive and Disjunctive Version Spaces

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Artificial Intelligence: Methodology, Systems, and Applications (AIMSA 2000)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1904))

Abstract

The paper considers conjunctive and disjunctive version spa- ce learning as an incomplete search in complete hypotheses spaces. The incomplete search is guided by preference biases which are implemented by procedures based on the instance-based boundary sets representation of version spaces. The conditions for tractability of this representation are defined. As a result we propose to use instance-based boundary sets as a basis for the computationally feasible application of preference biases to version spaces.

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References

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Authors and Affiliations

  1. IKAT, Department of Computer Science, Maastricht University, P.O.BOX 616, 6200, MD, Maastricht, The Netherlands

    E. N. Smirnov & H. J. van den Herik

Authors
  1. E. N. Smirnov
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  2. H. J. van den Herik
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© 2000 Springer-Verlag Berlin Heidelberg

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Smirnov, E.N., van den Herik, H.J. (2000). Applying Preference Biases to Conjunctive and Disjunctive Version Spaces. In: Artificial Intelligence: Methodology, Systems, and Applications. AIMSA 2000. Lecture Notes in Computer Science, vol 1904. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45331-8_31

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  • DOI: https://doi.org/10.1007/3-540-45331-8_31

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-41044-7

  • Online ISBN: 978-3-540-45331-4

  • eBook Packages: Springer Book Archive

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