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International Conference on Inductive Logic Programming

ILP 2002: Inductive Logic Programming pp 254–269Cite as

Compact Representation of Knowledge Bases in ILP

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2583))

Abstract

Many inductive systems, including ILP systems, learn from a knowledge base that is structured around examples. In practical situations this example-centered representation can cause a lot of redundancy. For instance, when learning from episodes (e.g. from games), the knowledge base contains consecutive states of a world. Each state is usually described completely even though consecutive states may differ only slightly. Similar redundancies occur when the knowledge base stores examples that share common structures (e.g. when representing complex objects as machines or molecules). These two types of redundancies can place a heavy burden on memory resources. In this paper we propose a method for representing knowledge bases in a more effcient way. This is accomplished by building a graph that implicitly defines examples in terms of other structures. We evaluate our method in the context of learning a Go heuristic.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Katholieke Universiteit Leuven, Celestijnenlaan 200A, B-3001, Leuven, Belgium

    Jan Struyf, Jan Ramon & Hendrik Blockeel

Authors
  1. Jan Struyf
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  2. Jan Ramon
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  3. Hendrik Blockeel
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Editor information

Editors and Affiliations

  1. School of Information Technology and Engineering, University of Ottawa, 800 King Edward Ave., K1N 6N5, Ottawa, ON, Canada

    Stan Matwin

  2. School of Computer Science and Engineering, University of New South Wales, 2052, Sydney, NSW, Australia

    Claude Sammut

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© 2003 Springer-Verlag Berlin Heidelberg

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Struyf, J., Ramon, J., Blockeel, H. (2003). Compact Representation of Knowledge Bases in ILP. In: Matwin, S., Sammut, C. (eds) Inductive Logic Programming. ILP 2002. Lecture Notes in Computer Science(), vol 2583. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36468-4_17

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  • DOI: https://doi.org/10.1007/3-540-36468-4_17

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-00567-4

  • Online ISBN: 978-3-540-36468-9

  • eBook Packages: Springer Book Archive

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