An efficient propositional system for Abductive Logic Programming
Abstract Abductive logic programming (ALP) extends logic programming with hypothetical reasoning by means of abducibles, an extension able to handle interesting problems, such as diagnosis, planning, and verification with formal methods. Implementations of this extension have been using Prolog meta-interpreters and Prolog programs with Constraint Handling Rules (). While the latter adds a clean and efficient interface to the host system, it still suffers in performance for large programs. Here, the concern is to obtain a more performant implementation of the system following a compiled approach. This paper, as a first step in this long term goal, sets out a propositional ALP system following , eliminating the need for and achieving better performance.
Authors
- Pascual Julián-Iranzo (ORCID: https://orcid.org/0000-0002-6482-3220)
- Fernando Sáenz-Pérez (ORCID: https://orcid.org/0000-0001-6075-4398)
- Marco Gavanelli (ORCID: https://orcid.org/0000-0001-7433-5899)
Institutions
- Universidad Complutense de Madrid (ES)
- University of Ferrara (IT)
- University of Castilla-La Mancha (ES)
- Software (Spain) (ES)
Publication Details
- Journal
- Artificial Intelligence Review
- Published
- 2024-10-17
- DOI
- https://doi.org/10.1007/s10462-024-10928-7
- Primary Topic
- Logic, Reasoning, and Knowledge
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Comunidad de Madrid
- European Commission
- Ministerio de Ciencia e Innovación
- Università degli Studi di Ferrara
- Gruppo Nazionale per il Calcolo Scientifico
- Agencia Estatal de Investigación