智能环境中的群体智能:从复杂性到集体性的旅程

I. Ananta, V. Callaghan, J. Chin, Matthew Ball, M. Gardner
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引用次数: 2

摘要

智能环境中复杂性的一种形式来自于它们的异构性。从理论上讲,日益多样化的环境和操作智能环境的无数用户的刻板印象将增加使用它们所需的复杂性和资源。然而,我们认为在智能环境中利用群体智能技术为处理这些复杂性提供了几个优势。介绍了一种称为基于人群的异构环境框架(CHAMBER)的新架构,它提出使用分层聚类来发现单个智能环境的基础设施之间的相似性,然后将其提供给希望构建自己的智能环境的其他用户使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Crowd Intelligence in Intelligent Environments: A Journey from Complexity to Collectivity
One form of complexity in intelligent environments arises from their heterogeneous nature. The growing variety of environments and countless stereotypes of users operating Intelligent Environments will, theoretically, increase the complexity and resources needed to utilise them. However we argue that utilizing Crowd Intelligence techniques in Intelligent Environments offer several advantages for dealing with these complexities. A novel architecture called a Crowd Based Heterogeneous Ambient Environment Framework (CHAMBER) is introduced, which proposes the use of hierarchical clustering to discover similarities between the infrastructures of individual Intelligent Environments, which are then offered for use by other users wishing to construct their own intelligent environments.
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