An efficient propositional system for Abductive Logic Programming

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-interpret...

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Bibliographic Details
Published in:The Artificial intelligence review Vol. 57; no. 12; p. 334
Main Authors: Gavanelli, Marco, Julián-Iranzo, Pascual, Sáenz-Pérez, Fernando
Format: Journal Article
Language:English
Published: Dordrecht Springer Netherlands 01.12.2024
Springer
Springer Nature B.V
Subjects:
Artificial Intelligence
Computer Science
Formal method
Hypotheses
Interpreters
Logic
Logic programming
Medical diagnosis
Prolog
Semantics
Verification
SCIFF
Hypothetical Reasoning
Abductive Logic Programming
System Implementation
ISSN:1573-7462, 0269-2821, 1573-7462
Online Access:Get full text
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Summary: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 (CHR). 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 SCIFF system following a compiled approach. This paper, as a first step in this long term goal, sets out a propositional ALP system following SCIFF, eliminating the need for CHR and achieving better performance.
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ISSN:1573-7462
0269-2821
1573-7462
DOI:10.1007/s10462-024-10928-7