Abstract
This paper presents a method of extracting subprograms from background knowledge. Most studies on learning logic programs so far developed are mainly concerned with pure Prolog, so that we can not deal with programs with system predicates such as the cut symbol, true, false, and so on. Explanation-based generalization system builds an explanation and learns a concept definition as its generalization, provided an input program. However, it assumes the input program be pure Prolog program. This paper proposes explanation-based reuse (EBR, for short), which is an extension of the explanation-based generalization and a method of program reuse. In EBR, we can deal with some system predicates. In extracting subprograms, we need to extract correct subprograms based on not only an explanation but also the whole back-ground knowledge for a goal concept. This paper also shows that such extracted subprograms by EBR are correct.
This work is partly supported by Grants-in-Aid for JSPS fellows and Scientific Research on Priority Areas from the Ministry of Education, Science and Culture, Japan
JSPS Fellowship for Japanese Junior Scientists
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© 1994 Springer-Verlag Berlin Heidelberg
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Koga, Y., Hirowatari, E., Arikawa, S. (1994). Explanation-based reuse of prolog programs. In: Arikawa, S., Jantke, K.P. (eds) Algorithmic Learning Theory. AII ALT 1994 1994. Lecture Notes in Computer Science, vol 872. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-58520-6_61
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DOI: https://doi.org/10.1007/3-540-58520-6_61
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