A sound and complete semantics for a similarity-based logic programming language

Julián-Iranzo, Pascual; Rubio-Manzano, Clemente

doi:10.1016/j.fss.2016.12.016

Cited by 23 publications

(5 citation statements)

References 19 publications

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“…Bousi∼Prolog (BPL) [15,8] is a fuzzy logic programming language that replaces syntactic unification of classical SLD-resolution by a fuzzy unification algorithm. This algorithm provides a weak most general unifier and a corresponding unification degree (which takes a numeric value between 0 and 1).…”

Section: Integration Into Bousi∼prologmentioning

confidence: 99%

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WordNet and Prolog: why not?

Julián-Iranzo

Sáenz-Pérez

2019

Proceedings of the 2019 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and

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This paper describes a set of Prolog modules with predicates to access the information stored in the lexical database WordNet. The aim is to use the defined predicates for empowering (fuzzy) logic programming systems for approximate reasoning tasks. To achieve this goal it is necessary to have means to calculate the degree of relationship between the words. Because WordNet relates words but does not give graded information of the relation between those words, it is necessary to implement standard methods to compute that gradation.

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Section: Integration Into Bousi∼prologmentioning

confidence: 99%

“…(fuzzy) logic programming system implemented in Prolog. As an additional motivation for this work, we have incorporated this library into the Bousi∼Prolog fuzzy logic programming system [15,8] to facilitate approximate reasoning tasks and a more flexible query answering process.…”

Section: Introductionmentioning

confidence: 99%

WordNet and Prolog: why not?

Julián-Iranzo

Sáenz-Pérez

2019

Proceedings of the 2019 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and

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“…Although there has been some research work on resolution-based automated reasoning methods based on non-classical logic (e.g., for fuzzy logic and many-valued logic) as cited earlier, the essential idea in many of those methods is to transform the resolution algorithm in fuzzy logic and many-valued logic to that of classical logic, because there is no constant formula involved in the syntax of the logic system so they have the syntactical equivalence, this is one of the key differences form the automated deduction in signed logic or annotated logic [20,44,56,57,81,82] , Bilattice-based logics [83] , probabilistic logic [84], similarity-based logic [85] . The works related to Lukasiewicz logic have been mainly focused on generalized CNF based on bold product and bold sum operators or logic programming [59,76,77] .…”

Section: Related Workmentioning

confidence: 99%

Non-Clausal Multi-ary α-Generalized Resolution Calculus for a Finite Lattice-Valued Logic

Xu¹,

Li²,

He³

et al. 2018

IJCIS

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Due to the need of the logical foundation for uncertain information processing, development of efficient automated reasoning system based on non-classical logics is always an active research area. The present paper focuses on the resolution-based automated reasoning theory in a many-valued logic with truth-values defined in a lattice-ordered many-valued algebraic structure -lattice implication algebras (LIA). Specifically, as a continuation and extension of the established work on binary resolution at a certain truth-value level α (called α-resolution), a non-clausal multi-ary α-generalized resolution calculus is introduced for a lattice-valued propositional logic LP(X) based on LIA, which is essentially a non-clausal generalized resolution avoiding reduction to normal clausal form. The new resolution calculus in LP(X) is then proved to be sound and complete. The concepts and theoretical results are further extended and established in the corresponding lattice-valued first-order logic LF(X) based on LIA.

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“…[24] it is used to solve a traditional AI problem that is the SAT solvers [20,24] and in [27] shows performing queries on ontologies with the OWL 1 standard. Finally we can see the we saw the different variantsof this language like Golog [20], the Prolog [28] and some implementations in Java and frameworks [29,30 we show how Prolog can be used to define rules over a space and determine the consistency in a knowledge base. Section 2, contains some theorical considerations about topologic spatial relations and information about the RCC model.…”

Section: Qualitative Reasoningmentioning

confidence: 99%

“…Prolog have a wide application as an see in [21], it can be used to perform a Case Based Reasoning to construct a representation to define the properties of a waste treatment in order to know the similarities between the cases. [24] it is used to solve a traditional AI problem that is the SAT solvers [20, an application performing queries on importance of Prologwether we saw the different variant extension Bousi-Prolog [28] and some implement…”

Section: Introductionmentioning

confidence: 99%

Prologused to Represent and Reason Qualitatively Over a Space Domain

Loza-Pacheco¹,

Torrez-Ruiz²,

Guzmán³

et al. 2017

IJAIA

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Spatial reasoning is a relevant topic in artificial intelligence with applications in geographical Information System, robotics, content-based image retrieval, traffic engineering. Additionally formal representation of knowledge allows the processing in a computer. Prolog is a programming language used in artificial intelligence that is useful to represent knowledge and perform a search, by asking questions in the knowledge base. Prolog can be used to develop a variety of applications like check the consistency or to perform any kind of reasoning. This article proposes the use of Prolog as a representation model and a reasoning engine to describe the topological relations between several objects in a geographic space, using the RCC model. The application of this simplifies the constructionprogram, allows us to focus on the spatial problem.

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A sound and complete semantics for a similarity-based logic programming language

Cited by 23 publications

References 19 publications

WordNet and Prolog: why not?

WordNet and Prolog: why not?

Non-Clausal Multi-ary α-Generalized Resolution Calculus for a Finite Lattice-Valued Logic

Prologused to Represent and Reason Qualitatively Over a Space Domain

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