Relating function of complex networks to structure using information theory

使用信息论将复杂网络的功能与结构联系起来

• 批准号: DE160100630
• 负责人: A/Prof Joseph Lizier
• 金额: $ 26.28万
• 依托单位: The University of Sydney
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Early Career Researcher Award
• 财政年份: 2016
• 资助国家: 澳大利亚
• 起止时间: 2016-06-30 至 2019-12-31
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DE160100630
• 关键词: Relating; function; complex; networks; structure

This project aims to investigate networks in order to translate network function to a universal language of information flows. Network science has used common tools to reveal universal connection structures within various biological and man-made networks – our brains, social networks and power grids are all networks of interacting components. Yet there is no common method to study the function of these networks and how such function is coupled with structure. This project aims to relate network structure to function by using measures of information processing as a generally-applicable framework. This will deliver a theory of how structure gives rise to dynamics and how structure can be optimised for desired dynamics.

该项目旨在研究网络，以便将网络功能转化为信息流的通用语言。网络科学使用通用的工具来揭示各种生物和人造网络中的普遍连接结构——我们的大脑、社会网络和电网都是相互作用的组成部分。然而，目前还没有通用的方法来研究这些网络的功能以及这些功能如何与结构耦合。该项目旨在通过使用信息处理措施作为普遍适用的框架，将网络结构与功能联系起来。这将提供结构如何产生动力学的理论，以及如何优化结构以获得所需的动力学。