DNF Hypotheses in Explanatory Induction

  • Katsumi Inoue
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7207)

Abstract

This paper investigates the problem of computing hypotheses in disjunctive normal form (DNF) for explanatory induction. This is contrasted to the usual setting of ILP, where hypotheses are obtained in conjunctive normal form (CNF), i.e., a set of clauses. We present two approaches to compute DNF hypotheses as well as several sound and complete algorithms. This problem naturally contains abduction from clausal theories, and can be related to model-based inductive reasoning, in which propositional reasoning methods such as SAT techniques and prime implicant computation can be utilized.

Keywords

Conjunctive Normal Form Inductive Logic Programming Disjunctive Normal Form Weak Hypothesis Conjunctive Normal Form Formula 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Katsumi Inoue
    • 1
  1. 1.National Institute of InformaticsChiyoda-kuJapan

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