This is just for informing that the new release of:
Bousi~Prolog version 3.2
has been launched on April, 6th, 2019, and tested for:
SWI-Prolog 7.6.4 running on:
Ubuntu 18 LTS,
Windows 10, and
macOS High Sierra
Bousi~Prolog (BPL) is a fuzzy logic programming language that replaces the syntactic unification mechanism of classical SLD-resolution by a fuzzy unification algorithm. This algorithm provides a weak most general unifier as well as a numerical value, called the unification degree. Intuitively, the unification degree represents the truth degree associated with the (query) computed instance. Then, the core of BPL operational semantics is a fuzzy unification algorithm based on proximity relations (that is a reflexive and symmetric, but not necessarily transitive, binary fuzzy relation on a set). Hence generalizing the operational mechanism of [Se2006], based on similarity relations, and increasing the expressive power of the resulting language. Proximity relations allow us to model problems where the transitivity restriction of a similarity relation is an obstacle.
In addition to proximity relations, BPL provides directives for defining fuzzy subsets, which give semantics to linguistic terms and are a valuable resource for modeling vagueness. Recently, a connection to the WordNet lexical database has been developed.
The current version has reached a new degree of maturity. The system is more stable and a number of small errors have been fixed. However, the main novelty of this version has been the incorporation of filtering techniques that optimize the TPL code generated after the parsing phase. Also, fuzzy modifiers can be applied on predicate symbols.
Executables and installers for different OS’s can be downloaded from:
Also, an on-line (prototype) system is also available at:
Pascual Julián-Iranzo and Fernando Sáenz-Pérez
[JR2015] Pascual Julián-Iranzo and Clemente Rubio-Manzano (2015). “Proximity-based unification theory”. Fuzzy Sets Syst. 262, C (March 2015), 21-43.
[JR2017] Pascual Julián Iranzo and Clemente Rubio-Manzano (2017). “A sound and complete semantics for a similarity-based logic programming language”. Fuzzy Sets and Systems 317:1-26.
[JS2018] Pascual Julián-Iranzo and Fernando Sáenz-Pérez (2018). “An Efficient Proximity-based Unification Algorithm”. 2018 IEEE International Conference on Fuzzy Systems.
[JS2019] Pascual Julián-Iranzo and Fernando Sáenz-Pérez (2019). “WordNet Measures of Lexical Semantic Relatedness in a Fuzzy Logic Programming System”. [Submitted]
[RJ2014] Clemente Rubio-Manzano and Pascual Julián-Iranzo (2014). “A Fuzzy linguistic Prolog and its applications”. Journal of Intelligent and Fuzzy Systems 26(3): 1503-1516.
[Se2002] Maria I. Sessa, “Approximate reasoning by similarity-based SLD resolution”, Theoretical Computer Science, vol. 275, no. 1-2, pp. 389–426, 2002.