Abstract
Commonsense reasoning and machine learning are two important topics in AI. These techniques are realized in logic programming as nonmonotonic logic programming (NMLP) and inductive logic programming (ILP), respectively. NMLP and ILP have seemingly different motivations and goals, but they have much in common in the background of problems. This article overviews the author’s recent research results for realizing induction from nonmonotonic logic programs.
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Sakama, C. (2002). Towards the Integration of Inductive and Nonmonotonic Logic Programming. In: Arikawa, S., Shinohara, A. (eds) Progress in Discovery Science. Lecture Notes in Computer Science(), vol 2281. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45884-0_10
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DOI: https://doi.org/10.1007/3-540-45884-0_10
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