An overview of the ABC Repair System for Datalog-like Theories

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

Abstract / Description of output

Humans are smart in revising their knowledge and concepts based on observations when they find conflicts. This ability to repair representations is also important for AI agents so that they can represent their environment correctly. This paper gives an overview of the domain-independent ABC system for repairing faulty logical theories by combining three existing techniques: abduction, belief revision and conceptual change. (A) Given an observation, represented as an assertion, and a current theory, abduction adds axioms, or deletes preconditions, which explain that observation by making the corresponding assertion derivable from the expanded theory. (B) Belief revision incorporates a new piece of information which conflicts with the input theory by either deleting old axioms or adding new preconditions to them. (C) Conceptual change uses the reformation algorithm for blocking unwanted proofs or unblocking wanted proofs. The former two techniques change an axiom as a whole, while reformation changes the language in which the theory is written. These three techniques are complementary so they are combined into one system: the ABC repair system, which is capable of repairing logical theories with better result than each individual technique alone and has been applied to applications in multiple domains. Datalog is used as ABC’s underlying logic of theories, but the proposed system has the potential to be adapted to theories in other logics.
Original languageEnglish
Title of host publicationProceedings of 3rd International Workshop on Human-Like ComputingHLC2022 @ IJCLR
EditorsAlan Bundy, Denis Mareschal
PublisherCEUR Workshop Proceedings (
Number of pages7
Publication statusPublished - 2 Oct 2022
EventThe 3rd International Workshop on Human-Like Computing 2022 - Windsor, United Kingdom
Duration: 28 Sept 202230 Sept 2022
Conference number: 3

Publication series

NameHuman-Like Computing Workshop 2022
PublisherCEUR Workshop Proceedings
ISSN (Electronic)1613-0073


WorkshopThe 3rd International Workshop on Human-Like Computing 2022
Abbreviated titleHLC 2022
Country/TerritoryUnited Kingdom
Internet address

Keywords / Materials (for Non-textual outputs)

  • Automated theory repair
  • Abduction
  • Belief revision
  • Conceptual change
  • Reformation
  • Knowledge representation
  • Automated reasoning


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