基于智能代理的电子学习系统的学习算法

N. Pandey, Shashank Sahu, R. K. Tyagi, A. Dwivedi
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引用次数: 10

摘要

需求是使项目得以成功实施的基本实体。在软件开发过程中,必须准确、正确地测量这些需求。最终用户的需求可能会根据不同的个体个性而改变。由于不同的客户有不同的需求,单个软件系统无法处理所有的需求。在这种情况下,必须在软件系统中自动进行更改,以满足用户的所有需求。具有智能主体的系统可以满足这一条件。本文提出了智能代理顾问代理、个性化代理和内容管理代理的算法来自动收集和满足学生的需求。算法是使用强化学习构建的。这些算法使智能体能够感知学生的需求,并在其运行过程中不断进化。这些智能代理是在部署电子学习软件后应用的。所有算法均已成功实现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Learning algorithms For intelligent agents based e-learning system
Requirements are the basic entity which makes the project to be successfully implemented. In the development of the software, theses requirements must be measured accurately and correctly. The requirements of the end users may be changed with respect to different individual personality. As different requirements are given by different customers, all of them cannot be processed by single software system. In such a case, it is essential to make the changes in the software systems automatically which fulfills all the requirements of the user. Such condition is met by the systems with intelligent agents. In this paper, algorithms of intelligent agents adviser agent, personalization agent and content managing agent are proposed to automatically gather the requirements of the students and fulfill them. The algorithms are structured using reinforcement learning. Theses algorithm makes the agents to sense the needs of the students and evolve in the course of their operation. These intelligent agents are applied after the deployment of the e-learning software. All the algorithms have been implemented successfully.
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