ACUOS2: A High-Performance System for Modular ACU Generalization with Subtyping and Inheritance

María Alpuente, Demis Ballis, Angel Cuenca-Ortega, Santiago Escobar, José Meseguer

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

Abstract

Generalization in order-sorted theories with any combination of associativity (A), commutativity (C), and unity (U) algebraic axioms is finitary. However, existing tools for computing generalizers (also called “anti-unifiers”) of two typed structures in such theories do not currently scale to real size problems. This paper describes the ACUOS2 system that achieves high performance when computing a complete and minimal set of least general generalizations in these theories. We discuss how it can be used to address artificial intelligence (AI) problems that are representable as order-sorted ACU generalization, e.g., generalization in lists, trees, (multi-)sets, and typical hierarchical/structural relations. Experimental results demonstrate that ACUOS2 greatly outperforms the predecessor tool ACUOS by running up to five orders of magnitude faster.

Original languageEnglish (US)
Title of host publicationLogics in Artificial Intelligence - 16th European Conference, JELIA 2019, Proceedings
EditorsFrancesco Calimeri, Nicola Leone, Marco Manna
PublisherSpringer
Pages171-181
Number of pages11
ISBN (Print)9783030195694
DOIs
StatePublished - 2019
Event16th European Conference on Logics in Artificial Intelligence, JELIA 2019 - Rende, Italy
Duration: May 7 2019May 11 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11468 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference16th European Conference on Logics in Artificial Intelligence, JELIA 2019
Country/TerritoryItaly
CityRende
Period5/7/195/11/19

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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