Modeling Uncertainty and Imprecision in Nonmonotonic Reasoning using Fuzzy Numbers

Fuzzy Logic in Narrow Sense with Hedges

Classical logic has a serious limitation in that it cannot cope with the issues of vagueness and uncertainty into which fall most modes of human reasoning. In order to provide a foundation for human knowledge representation and reasoning in the presence of vagueness, imprecision, and uncertainty, fuzzy logic should have the ability to deal with linguistic hedges, which play a very important role in the modification of fuzzy predicates. In this paper, we extend fuzzy logic in narrow sense with graded syntax, introduced by Novak et al., with many hedge connectives. In one case, each hedge does n…

A Modelling Approach Based on Fuzzy Agents

Modelling of complex systems is mainly based on the decomposition of these systems in autonomous elements, and the identification and definitio9n of possible interactions between these elements. For this, the agent-based approach is a modelling solution often proposed. Complexity can also be due to external events or internal to systems, whose main characteristics are uncertainty, imprecision, or whose perception is subjective (i.e. interpreted). Insofar as fuzzy logic provides a solution for modelling uncertainty, the concept of fuzzy agent can model both the complexity and uncertainty. This …

An Empirical Approach for Modeling Fuzzy Geographical Descriptors

We present a novel heuristic approach that defines fuzzy geographical descriptors using data gathered from a survey with human subjects. The participants were asked to provide graphical interpretations of the descriptors `north' and `south' for the Galician region (Spain). Based on these interpretations, our approach builds fuzzy descriptors that are able to compute membership degrees for geographical locations. We evaluated our approach in terms of efficiency and precision. The fuzzy descriptors are meant to be used as the cornerstones of a geographical referring expression generation algorit…

On modeling vagueness and uncertainty in data-to-text systems through fuzzy sets

Vagueness and uncertainty management is counted among one of the challenges that remain unresolved in systems that generate texts from non-linguistic data, known as data-to-text systems. In the last decade, work in fuzzy linguistic summarization and description of data has raised the interest of using fuzzy sets to model and manage the imprecision of human language in data-to-text systems. However, despite some research in this direction, there has not been an actual clear discussion and justification on how fuzzy sets can contribute to data-to-text for modeling vagueness and uncertainty in wo…

使用区间二型模糊推理系统与多专家决策的驾驶风格识别

Driving Style Recognition Using Interval Type-2 Fuzzy Inference System and Multiple Experts Decision Making

本文提出一种基于区间二型模糊推理系统与多专家决策的驾驶风格识别方法，将驾驶员分为平静、中等和激进三类，实验表明该方法倾向于识别较低运动学特征的驾驶风格，且比一型模糊系统更鲁棒。

Learner to learner fuzzy profiles similarity using a hybrid interaction analysis grid

The analysis of remote discussions is not yet at the same level as the face-to-face ones. The present paper aspires twofold. On the one hand, it attempts to establish a suitable environment of interaction and collaboration among learners by using the speech acts via a semi structured synchronous communication tool. On the other, it aims to define behavioral profiles and interpersonal skills hybrid grid by matching the BALES' IPA and PLETY's analysis system. By applying the fuzzy logic, we formalize human reasoning and, thus, giving very appreciable flexibility to the reasoning that use it, whi…

构建区间型模糊隶属函数：基于扑克牌的共构方法

Building Interval Type-2 Fuzzy Membership Function: A Deck of Cards based Co-constructive Approach

本文提出一种基于扑克牌的共构方法，用于构建区间型模糊隶属函数，以提高多准则决策中对决策者犹豫和模糊性的处理能力。