Bousi∼Prolog: Design and implementation of a proximity-based fuzzy logic programming language

The fuzzy logic programming language Bousi∼Prolog extends Prolog with a weak unification algorithm based on proximity relations and truth degree annotations. The weak unification algorithm makes the search for answers more flexible, while rule annotations make possible knowledge-based applications w...

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Bibliographic Details
Published in:Expert systems with applications Vol. 213; p. 118858
Main Authors: Julián-Iranzo, Pascual, Sáenz-Pérez, Fernando
Format: Journal Article
Language:English
Published: Elsevier Ltd 01.03.2023
Subjects:
Bousi∼Prolog
Fuzzy logic programming
Fuzzy prolog
Proximity relations
Weak SLD resolution
Weak unification
Fuzzy prolog
Weak unification
Weak SLD resolution
Fuzzy logic programming
Proximity relations
Bousi∼Prolog
ISSN:0957-4174, 1873-6793
Online Access:Get full text
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Summary:The fuzzy logic programming language Bousi∼Prolog extends Prolog with a weak unification algorithm based on proximity relations and truth degree annotations. The weak unification algorithm makes the search for answers more flexible, while rule annotations make possible knowledge-based applications where the rules may be uncertain. In this paper, after recalling the main concepts supporting this language, we detail its design and implementation. We describe the implementation of its operational semantics, which is based on compiling programs and queries into Prolog, and those important features that makes it more applicable: fuzzy sets, integration with WordNet and efficiency techniques. The result is a high-level open-source implementation of the Bousi∼Prolog system, written on top of SWI-Prolog, and publicly available. We also summarise some experiments measuring its performance compared to other systems. •The fuzzy logic programming language Bousi∼Prolog is described.•Proximity relations, weak unification and graded rules allow for flexible queries.•The implementation of the operational semantics is described.•Novel efficiency techniques are applied at compile-time.•A performance comparison with other systems shows its relevance.
ISSN:0957-4174
1873-6793
DOI:10.1016/j.eswa.2022.118858