Towards meta-interpretive learning of programming language semantics

Sándor Bartha, James Cheney

Research output: Chapter in Book/Report/Conference proceedingConference contribution


We introduce a new application for inductive logic programming: learning the semantics of programming languages from example evaluations. In this short paper, we explored a simplified task in this domain using the Metagol meta-interpretive learning system. We highlighted the challenging aspects of this scenario, including abstracting over function symbols, nonterminating examples, and learning non-observed predicates, and proposed extensions to Metagol helpful for overcoming these challenges, which may prove useful in other domains.
Original languageEnglish
Title of host publicationInductive Logic Programming
Subtitle of host publication29th International Conference, ILP 2019, Plovdiv, Bulgaria, September 3–5, 2019, Proceedings
EditorsDimitar Kazakov, Can Erten
PublisherSpringer, Cham
Number of pages10
ISBN (Electronic)978-3-030-49210-6
ISBN (Print)978-3-030-49209-0
Publication statusPublished - 5 Jun 2020
Event29th International Conference on Inductive Logic Programming - Plovdiv, Bulgaria
Duration: 3 Sep 20195 Sep 2019

Publication series

NameLecture Notes in Computer Science
PublisherSpringer, Cham
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference29th International Conference on Inductive Logic Programming
Abbreviated titleILP 2019
Internet address


  • cs.PL
  • cs.LG
  • cs.LO

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