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On the Complexity of Inductively Learning Guarded Rules

arXiv 2110.03624 ↗First posted 7 Oct 2021cs.CC cs.AIcited by 0

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Abstract (arXiv)

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 σP2-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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References · 3

  1. 2020Turning 30: New Ideas in Inductive Logic Programmingcited by 42
  2. 2018The Vadalog System: Datalog-based Reasoning for Knowledge Graphscited by 25
  3. 2019Synthesizing Datalog Programs Using Numerical Relaxationcited by 23

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