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GoslerP — A logic programming tool for inductive inference

  • 2 Inductive Inference for Artificial Intelligence
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Algorithmic Learning for Knowledge-Based Systems

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 961))

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Abstract

This paper starts from the following task: Logic programming is to be connected with a declarative concept of database changes. The theory of inductive inference is considered as the domain of application. Learning processes are characterized by hypothetical knowledge and by permanent changes of this knowledge. Finally, the target consists in the creation of GoslerP, a tool of logic programming, which is usable for the modelling of knowledge based learning processes and the implementation of learning algorithms. GoslerP is an extension of Prolog. At the end of the paper, the new possibilities for learning are demonstrated by a first simple application.

The work has been supported by the German Ministry for Research and Technology (BMFT) within the joint project GOSLER (no. 413-4001-01 IW 101 D).

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Authors and Affiliations

  1. Institute of Informatics, Humboldt University of Berlin, 10099, Berlin, Germany

    Hans -Rainer Beick & Ventsislav Stankov

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  1. Hans -Rainer Beick
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  2. Ventsislav Stankov
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Klaus P. Jantke Steffen Lange

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© 1995 Springer-Verlag Berlin Heidelberg

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Beick, H.R., Stankov, V. (1995). GoslerP — A logic programming tool for inductive inference. In: Jantke, K.P., Lange, S. (eds) Algorithmic Learning for Knowledge-Based Systems. Lecture Notes in Computer Science, vol 961. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-60217-8_23

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  • DOI: https://doi.org/10.1007/3-540-60217-8_23

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-60217-0

  • Online ISBN: 978-3-540-44737-5

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