基于网格的社会学习多智能体系统的开发

C. Kiourt, Dimitris Kalles
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引用次数: 3

摘要

在本文中,我们提出了一种新的架构,用于简化部署在网格上的多智能体系统的人类专家管理,目的是研究社会学习。通过数据同步实用程序,网格提供的通信服务与管理层和传统web服务器编程相耦合,导致基于web的用户界面的直接开发,该界面允许监视和管理各种在线分布式计算应用程序。最后,我们提出了一些实验结果,以强调我们认为表明这样一个平台的实验规模。我们的实现已经开发出来,可以部署在现有的网格基础设施上,而不会影响安全性。
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Development of grid-based multi agent systems for social learning
In this paper we present a novel architecture for streamlining human expert management for a multi agent system deployed at the grid with the objective of investigating social learning. The coupling of the communication services offered by the grid, with an administration layer and conventional web server programming, via a data synchronization utility, leads to the straightforward development of a web-based user interface that allows the monitoring and managing of diverse online distributed computing applications. Finally, we present some experimental results to underline the scale of experiments we view as indicative of such a platform. Our implementation has been developed and can be deployed over existing grid infrastructures without compromising security.
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