On the Complexity of Inductively Learning Guarded Rules

Andrei Draghici; Georg Gottlob; Matthias Lanzinger

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arXiv · 2110.03624

On the Complexity of Inductively Learning Guarded Rules

Andrei Draghici·Georg Gottlob·Matthias Lanzinger

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Abstract

We investigate the computational complexity of mining guarded clauses from clausal datasets through the framework of inductive logic programming (ILP). We show that learning guarded clauses is NP-complete and thus one step below the $\sigma^P_2$-complete task of learning Horn clauses on the polynomial hierarchy. Motivated by practical applications on large datasets we identify a natural tractable fragment of the problem. Finally, we also generalise all of our results to $k$-guarded clauses for constant $k$.

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BibTeX RIS

Andrei Draghici, Georg Gottlob, Matthias Lanzinger. 2021-10-07. On the Complexity of Inductively Learning Guarded Rules. https://arxiv.org/abs/2110.03624

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