Fuzzy reasoning, case-based reasoning (CBR) and experience-based reasoning (EBR) or natural reasoning have been seriously studied for years. However, these studies essentially can be considered as a 1-dimensional approach, because their reasoning paradigm is 1-dimensional. This paper will propose a 2-dimensional (2D) approach that represents fuzzy reasoning, CBR, and EBR in a unified way. This ...

In this article, we describe the fuzzy logic, fuzzy language and algorithms as the basis of fuzzy reasoning, one of the intelligent information processing method, and then describe the general fuzzy reasoning method.

In the current paper we study the reasoning problem for fuzzy SI (f-SI) under arbitrary continuous fuzzy operators. Our work can be seen as an extension of previous works that studied reasoning algorithms for f-SI, but focused on specific fuzzy operators, e.g. fKD-SI and of reasoning algorithms for less expressive fuzzy DLs, like fL-ALC and fP -ALC (fuzzy ALC under the Lukasiewicz and product f...

In this paper, a fuzzy Petri net approach to modeling fuzzy rule-based reasoning is proposed to bring together the possibilistic entailment and the fuzzy reasoning to handle uncertain and imprecise information. The three key components in our fuzzy rule-based reasoning-fuzzy propositions, truth-qualified fuzzy rules, and truth-qualified fuzzy facts-can be formulated as fuzzy places, uncertain t...

In the paper a distance based operators based approximate reasoning method is represented, applying fuzzy measure. Distance based operators satisfy most of properties as generally defined parametrical operators. Based on this the possible relationship with the integrals based on fuzzy measures is introduced. It can be shown, that the reason used for fuzzy integral introduction is similar to the...

Reasoning in the presence of imprecision and vagueness is inevitable in many real-world applications including those in robotics and intelligent agents. Although, reasoning about actions is a major component in these real-world applications, current actions languages for reasoning about actions lack the ability to represent and reason about actions in the presence of imprecision and vagueness t...

The fuzzy extensions of description logics support representation and reasoning for fuzzy knowledge. But the current fuzzy description logics do not support the expression of comparisons between fuzzy membership degrees. The paper proposes ALCfc, a fuzzy extension of description logic ALC with comparison expressions. ALCfc defines comparison cut concepts to express complex comparisons, and inte...

By the development of Semantic Web, increasing demands for vague information representation have triggered a mass of theoretical and applied researches of fuzzy ontologies, whose main logical infrastructures are fuzzy description logics. However, current tableau algorithms can not supply complete reasoning support within fuzzy ontology: reasoning with general TBox is still a difficult problem i...

This paper discusses fuzzy reasoning for approximately realizing nonlinear functions by a small number of fuzzy if-then rules with different specificity levels. Our fuzzy rule base is a mixture of general and specific rules, which overlap with each other in the input space. General rules work as default rules in our fuzzy rule base. First we briefly describe existing approaches to the handling ...

– Approximate reasoning and fuzzy queries are efficient methods in retrieving information from large databases when precise attributes are unknown or the model itself is vague. We explore such types of reasoning based on the notions of the possibility theory. We suggest an approach towards a Prolog implementation of such queries which takes into account fuzzy linguistic quantification, aggregat...