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Infrastructure as a Complex Adaptive System

Authors: Oughton, EJ; Usher, W; Tyler, P; Hall, JW;

Infrastructure as a Complex Adaptive System

Abstract

National infrastructure systems spanning energy, transport, digital, waste, and water are well recognised as complex and interdependent. While some policy makers have been keen to adopt the narrative of complexity, the application of complexity‐based methods in public policy decision‐making has been restricted by the lack of innovation in associated methodologies and tools. In this paper we firstly evaluate the application of complex adaptive systems theory to infrastructure systems, comparing and contrasting this approach with traditional systems theory. We secondly identify five key theoretical properties of complex adaptive systems including adaptive agents, diverse agents, dynamics, irreversibility, and emergence, which are exhibited across three hierarchical levels ranging from agents, to networks, to systems. With these properties in mind, we then present a case study on the development of a system‐of‐systems modelling approach based on complex adaptive systems theory capable of modelling an emergent national infrastructure system, driven by agent‐level decisions with explicitly modelled interdependencies between energy, transport, digital, waste, and water. Indeed, the novel contribution of the paper is the articulation of the case study describing a decade of research which applies complex adaptive systems properties to the development of a national infrastructure system‐of‐systems model. This approach has been used by the UK National Infrastructure Commission to produce a National Infrastructure Assessment which is capable of coordinating infrastructure policy across a historically fragmented governance landscape spanning eight government departments. The application will continue to be pertinent moving forward due to the continuing complexity of interdependent infrastructure systems, particularly the challenges of increased electrification and the proliferation of the Internet of Things.

Country
United Kingdom
Related Organizations
Keywords

46 Information and Computing Sciences, Electronic computers. Computer science, 7 Affordable and Clean Energy, QA75.5-76.95, Generic health relevance

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
50
Top 10%
Top 10%
Top 10%