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Fuzzy Agent for Elearner Profile Construction

机译:Elearner简介建设的模糊代理

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In this paper, we describe the design and development of a fuzzy agent-based system for an elarning environment that is capable of effective delivery of personalized courseware to elearners. By personalization, we mean that two different persons registered at the same e-course with comparable learning paces will have two different behaviors from the system. For so doing, we want to address a specific issue. We mean that we are given a set of courses displayed on the Web, a set of disciplines to which these courses belong, a number of visiting times any prospective elearner makes to the Web site. It is desired to find the fuzzy membership of this specific elearner to the given disciplines, and a profile for this elearner capable of predicting his future behavior i.e. what this elearner is planning to do without letting him explicitly express his query. In order to address this issue, we propose to use fuzzy logic to express gradual and imprecise membership and agent paradigm to express autonomy for mapping percepts coming from the environment into correct actions under the control of the logic embodied within it. Furthermore, we use state of the art advanced tools for implementation based on two versions. The first version, a prototype, is implemented using Matlab. A second version using Microsoft.NET Technology, such as C#.NET. This results in the development of an advanced fuzzy agent-based system for elearner profile construction capable of predicting human behavior during the process of learning while offering an intelligent Graphical User Interface (GUI).
机译:在本文中,我们描述了一种基于模糊的代理的系统的设计和开发,可以为Elearners有效地提供个性化课件的elarning环境。通过个性化,我们的意思是,在相同的电子课程中注册的两个不同的人与可比的学习步伐将有两个来自系统的不同行为。为此,我们想要解决特定问题。我们的意思是,我们在网上展示了一组课程,这些课程所属的一套学科,任何潜在的Elearner都会到网站的访问时间。希望这一特定Elearner的模糊成员资格到给定的学科以及能够预测他未来行为的这种电子人的配置文件,即这是一个eLearner计划在不让他明确表达他的查询的情况下。为了解决这个问题,我们建议使用模糊逻辑来表达逐步和不精确的会员资格和代理范例,以表达自治,以便在控制内部所体现的逻辑的控制下映射到正确的行动。此外,我们使用最先进的先进工具来实现,以基于两个版本实现实现。使用MATLAB实现第一个版本,一种原型。使用Microsoft.Net技术的第二个版本,例如C#.NET。这导致开发用于Elearner简介施工的高级模糊代理系统,能够在学习过程中预测人类行为,同时提供智能图形用户界面(GUI)。

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