Results 251 to 260 of about 80,218 (288)

Induction of Fuzzy and Annotated Logic Programs

2007
The new direction of the research in the field of data mining is the development of methods to handle imperfection (uncertainty, vagueness, imprecision,...). The main interest in this research is focused on probability models. Besides these there is an extensive study of the phenomena of imperfection in fuzzy logic.
Peter Vojtáš, Tomáš Horváth
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Programming with Fuzzy Logic and Mathematical Functions

2006
This paper focuses on the integration of the (also integrated) declarative paradigms of functional logic and fuzzy logic programming, in order to obtain a richer and much more expressive framework where mathematical functions cohabit with fuzzy logic features.
Vicente Pascual, Ginés Moreno
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Annotated Fuzzy Logic Programming

2010
Fuzzy logic programming systems can be roughly classified into two groups with respect to whether they involve fuzzy sets in programs or not. Systems that do not involve fuzzy sets usually have fuzzy terms materialized as predicate symbols and formulas weighted by real numbers in the interval [0, 1], interpreted as truth or uncertainty degrees ...
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Constraint Logic Programming with Fuzzy Sets

1995
Constraint Logic Programming language embodying extensional finite Fuzzy Sets is presented. Basic fuzzy set operations (=, ∈, ≠, and ∉) are defined as constraints over fuzzy sets and their elements. Simple list-like representation of sets is presented, with fset/2 as the interpreted set constructor and {} as the empty set. Members of the fuzzy sets are
Hynek Bures, Ludek Matyska
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Fuzzy constraint logic programming: a proposal

Proceedings of 1995 IEEE International Conference on Fuzzy Systems. The International Joint Conference of the Fourth IEEE International Conference on Fuzzy Systems and The Second International Fuzzy Engineering Symposium, 2002
In this paper, we propose a new framework to integrate fuzzy logic programming and fuzzy mathematical programming. While fuzzy relation unifies fuzzy predicate and fuzzy constraint, the compositional rule of inference, when viewed in the right way, bridges the gap between a fuzzy logic clause and a fuzzy optimization formulation.
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Programming fuzzy logic in assembly language

IEEE Technical Applications Conference. Northcon/96. Conference Record, 2002
This paper outlines the subjects covered in a half-day class an programming fuzzy logic algorithms in assembly language. The short course covers assembly language examples that are not shown in this paper, and goes into much greater detail. Assembly language allows more efficient fuzzy logic programs in terms of code space and execution time compared ...
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Towards Categorical Fuzzy Logic Programming

2013
In this paper we investigate the shift from two-valued to many-valued logic programming, including extensions involving functorial and monadic constructions for sentences building upon terms. We will show that assigning uncertainty is far from trivial, and the place where uncertainty should be used is also not always clear.
Robert Helgesson, M. Ángeles Galán, Carlos Vazquez, Patrik Eklund, Jari Kortelainen, Ginés Moreno   +5 more
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A hybrid system combining intuitionistic fuzzy description logics with intuitionistic fuzzy logic programs

2011 Eighth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), 2011
In this paper, we present a novel combination of intuitionistic fuzzy Description Logics with intuitionistic fuzzy logic programs, which yields a more realistic and intelligent hybrid system, whitch offers the best of both aspects: the extension of Description Logics with intuitionistic fuzzy sets are suitable for describing vague and imprecise ...
Lian Shi, Shuai Lu, Dantong Ouyang, Tao Sun   +3 more
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Fuzzy FOIL: A fuzzy logic based inductive logic programming system.

1996
In many domains, characterizations of a given attribute are imprecise, uncertain and incomplete in the available learning examples. The definitions of classes may be vague. Learning systems are frequently forced to deal with such uncertainty. Traditional learning systems are designed to work in the domains where imprecision and uncertainty in the data ...
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Foundations of fuzzy logic programming and debugging

Proceedings. The Nineteenth International Symposium on Multiple-Valued Logic, 2003
A theoretical foundation is provided for programming in fuzzy Horn logic and declarative debugging in fuzzy Horn logic programming. Particular emphasis is placed on the study of the soundness and completeness for both. >
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