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Algebraic anti-unification

arXiv 2407.15510 ↗First posted 22 Jul 2024cs.AI cs.DM cs.LOcited by 0

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Abstract (arXiv)

Abstraction is key to human and artificial intelligence as it allows one to identify common structure in otherwise distinct objects or situations. Anti-unification (or generalization) is the branch of theoretical computer science and artificial intelligence that studies abstraction and has found applications in areas such as inductive logic programming, program synthesis, and analogy-making. To date, anti-unification has been studied almost exclusively from a syntactic perspective. In this paper, we initiate an algebraic (i.e. semantic) theory of anti-unification in the general setting of universal algebra, thereby extending anti-unification from term-based representations to arbitrary algebras and beyond equational theories. In particular, we introduce the notions of algebraic generalization ordering and minimally general generalization, establish basic structural properties, prove compatibility with homomorphisms and isomorphisms, and investigate computability in finite unary algebras and finite algebras via automata-theoretic methods.

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References · 13

  1. 2020Inductive logic programming at 30: a new introductioncited by 83
  2. 2020Learning programs by learning from failurescited by 73
  3. 2021Inductive logic programming at 30cited by 46
  4. 2022babble: Learning Better Abstractions with E-Graphs and Anti-Unificationcited by 22
  5. 2020Analogical proportionscited by 13
  6. 2018Logic program proportionscited by 12
  7. 2018Learning Quick Fixes from Code Repositoriescited by 8
  8. 2020Omission-based Abstraction for Answer Set Programscited by 7
  9. 2023Anti-unification and Generalization: A Surveycited by 7
  10. 2014E-Generalization Using Grammarscited by 3
  11. 2022Analogical proportions in monounary algebrascited by 2
  12. 2023Generalization-baed similaritycited by 2
1 more
  1. 2024Analogical proportions IIcited by 1

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