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Discovery of Abstract Concepts by a Robot

  • Conference paper
Algorithmic Learning Theory (ALT 2010)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6331))

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Abstract

This paper reviews experiments with an approach to discovery through robot’s experimentation in its environment. In addition to discovering laws that enable predictions, we are particularly interested in the mechanisms that enable the discovery of abstract concepts that are not explicitly observable in the measured data, such as the notions of a tool or stability. The approach is based on the use of Inductive Logic Programming. Examples of actually discovered abstract concepts in the experiments include the concepts of a movable object, an obstacle and a tool.

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Author information

Authors and Affiliations

  1. Faculty of Computer and Information Science, University of Ljubljana, Trz̀†as̀†ka 25, 1000, Ljubljana, Slovenia

    Ivan Bratko

Authors
  1. Ivan Bratko
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Editor information

Editors and Affiliations

  1. Research School of Information Sciences and Engineering, Australian National University and NICTA, 0200, Canberra, ACT, Australia

    Marcus Hutter

  2. Department of Mathematics, National University of Singapore, Block S17, 10 Lower Kent Ridge Road, 119076, Singapore, Republic of Singapore

    Frank Stephan

  3. Department of Computer Science, University of London, Royal Holloway, TW20 0EX, Egham, Surrey, UK

    Vladimir Vovk

  4. Division of Computer Science, Hokkaido University, , ,, N-14, W-9, Sapporo, 060-0814, Japan

    Thomas Zeugmann

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© 2010 Springer-Verlag Berlin Heidelberg

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Bratko, I. (2010). Discovery of Abstract Concepts by a Robot. In: Hutter, M., Stephan, F., Vovk, V., Zeugmann, T. (eds) Algorithmic Learning Theory. ALT 2010. Lecture Notes in Computer Science(), vol 6331. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16108-7_4

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  • DOI: https://doi.org/10.1007/978-3-642-16108-7_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-16107-0

  • Online ISBN: 978-3-642-16108-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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