Evolutionary Optimisation of Networks towards Complexity

网络向复杂性演化优化

• 批准号: EP/V048740/1
• 负责人: Jens Christian Claussen
• 金额: $ 25.75万
• 依托单位: Aston University
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FV048740%2F1
• 关键词: Evolutionary; Optimisation; Networks; towards; Complexity

Network science provides systematic approaches of introducing more complexity in the interaction topology, compared to random graphs as introduced by Erdös and Renyi. In which biological systems does a higher complexity result in improved resilience or other evolutionary benefits? Can this perspective provide insight for improving processes in technology and society? This project takes the novel approach of utilising network complexity measures to generate ensembles of networks of increasing complexity, followed up by an investigation into how network complexity influences the complexity of the resulting network dynamics. This approach is motivated by a common implicit hypothesis that complex structures are beneficial for adaptive systems, and aims to translate back beneficial complex network topologies into specific applications. It is expected that increased complexity can have a beneficial impact (as in networks evolved in nature), or might impede functionality (expected to appear in logistic or production networks) where benefits of resilience and adaptivity come at organisational costs of a more complex structure. The project therefore includes two application-oriented dynamical modelling studies where increased network performance from higher complexity is expected, but also investigates cases which might challenge the generality of such a paradigm.

与 Erdös 和 Renyi 引入的随机图相比，网络科学提供了在交互拓扑中引入更多复杂性的系统方法。在哪些生物系统中，更高的复杂性会导致恢复力的提高或其他进化益处？这种观点能否为改进技术和社会流程提供见解？该项目采用新颖的方法，利用网络复杂性度量来生成复杂性不断增加的网络集合，然后研究网络复杂性如何影响最终网络动态的复杂性。这种方法的动机是一个常见的隐含假设，即复杂结构有利于自适应系统，旨在将有益的复杂网络拓扑转化为特定应用。预计复杂性的增加可能会产生有益的影响（就像在自然界中进化的网络一样），或者可能会阻碍功能（预计会出现在物流或生产网络中），其中弹性和适应性的好处是以更复杂的结构的组织成本为代价的。因此，该项目包括两项面向应用的动态建模研究，预计通过更高的复杂性来提高网络性能，但也调查了可能挑战这种范例的普遍性的案例。