期刊文献+

移动代理人编程技术与移动用戶管理系统探讨(英文)

Maintaining Persistent Look-and-Feel for Roaming User with Mobile Agent in Distributed Environment
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摘要 有自我控制与辨别身份能力的移动代理人编程技术,不但能够在网路上移动,也能够与其他代理人编程沟通及执行任务.由于移动代理人常常运作于异质的网路或作业系统(operating system)环境下,因此,一个具有整体逻辑性操作界面来存取实体结构的管理系统就显得越发重要.提出了一个能够追踪和维持移动代理人的管理系统,并且应用于远距教学(distance learning).此系统的主要目的在于提供移动代理人通用的存取环境.为了能使此系统完全运作,论述了移动代理人通信网路模组、移动代理人演化阶段来支援管理代理人与用户端代理人.另外,也将移动代理人所使用的工具编程整合成为角色扮演(role-setting)物件;此角色扮演物件是符合所谓应用编程驱使元件(application-driven component)的,因此,此系统也能够符合专业化利益的使用者的需求. Mobile agents refer to self-contained and identifiable computer programs that can migrate along the network and can act on behalf of the user or other agents. Mobile agents often work on heterogeneous network and operating system environment. Therefore, an integrated logical interface to access physical structure via mobile agent application has become more and more urgent. In this paper, we proposed a tracking and persistent agent-based mobility management system in case of distance learning. The main purpose of our system is addressed to achieve the universal access objective. In order to let the whole mobility management system full play, firstly, we proposed a mobile agent communication network model and the mobile agent evolution states. The mobile agent communication network model facilitates the agent computation, and the mobile agent evolution states assist agent supervisor to monitor client agents. Secondly, we encapsulate the utility tools to be a role-setting object. The role-setting object is an application-driven component, which can provide customization benefits for user to match users demands. These integrated technologies are sufficient in distance learning (virtual university) environment.
出处 《软件学报》 EI CSCD 北大核心 2002年第5期887-889,共3页 Journal of Software
关键词 移动代理人 编程技术 移动用户管理系统 角色扮演 mobile agent agent communication network agent evolution states persistence look-and-feel client agent server agent
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参考文献1

  • 1Michael Pazzani,Daniel Billsus. Learning and Revising User Profiles: The Identification of Interesting Web Sites[J] 1997,Machine Learning(3):313~331

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