A Constraint Satisfaction Approach to Tractable Theory Induction

  • John Ahlgren
  • Shiu Yin Yuen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7997)


A novel framework for combining logical constraints with theory induction in Inductive Logic Programming is presented. The constraints are solved using a boolean satisfiability solver (SAT solver) to obtain a candidate solution. This speeds up induction by avoiding generation of unnecessary candidates with respect to the constraints. Moreover, using a complete SAT solver, search space exhaustion is always detectable, leading to faster small clause/base case induction. We run benchmarks using two constraints: input-output specification and search space pruning. The benchmarks suggest our constraint satisfaction approach can speed up theory induction by four orders of magnitude or more, making certain intractable problems tractable.


Inductive Logic Programming Theory induction Constraint satisfaction 



The work described in this paper was supported by a grant from the Research Grants Council of the Hong Kong Special Administrative Region, China [Project No. CityU 124409].


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.City University of Hong KongHong KongChina

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