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Inductive logic programming for discrete event systems

  • Session: Incremental Methods and Inductive Logic Programming
  • Conference paper
  • First Online:
Grammatical Interference: Learning Syntax from Sentences (ICGI 1996)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1147))

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Abstract

Inductive modelling of dynamic systems attempts to create a model for a system based on observed data. In this work we make possible that methods of Inductive Logic Programming (ILP) can be applied to induce the discrete-event specification of a system from its behaviour. The self-activation capacity of DEVS increases the complexity of this work by introducing time-dependent conditions in the transition functions. Besides, we will show how a new set of “state variables” can be derived from the time-dependent data when the initial set is not sufficiently relevant.

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References

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Authors and Affiliations

  1. Computer Science Dept., University of A Coruña, Spain

    David Lorenzo

Authors
  1. David Lorenzo
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Editor information

Laurent Miclet Colin de la Higuera

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© 1996 Springer-Verlag Berlin Heidelberg

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Lorenzo, D. (1996). Inductive logic programming for discrete event systems. In: Miclet, L., de la Higuera, C. (eds) Grammatical Interference: Learning Syntax from Sentences. ICGI 1996. Lecture Notes in Computer Science, vol 1147. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0033359

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  • DOI: https://doi.org/10.1007/BFb0033359

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-61778-5

  • Online ISBN: 978-3-540-70678-6

  • eBook Packages: Springer Book Archive

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