Johnson, J. H.
|DOI (Digital Object Identifier) Link:||https://doi.org/10.1057/palgrave.rm.8250023|
|Google Scholar:||Look up in Google Scholar|
Undesirable rare and new events are hard to predict and their costs are hard to quantify. The science of complex systems gives deep insights into why some events are impossible to predict in the long term. Computer simulation is evolving as a way to understand the behaviour of complex systems and can be used to investigate distributions of rare events and risks. Simulation has its own risks; for example, the “ can you trust it? ” problem means that simulations can be misleading. Many complex systems have multi-dimensional multi-level structure, with Type-1 dynamics represented by changes in numerical functions, and Type-2 dynamics, represented by changes in relational structure. This may help to analyse and manage risk. The science of complex systems will increasingly inform those who design, manage, plan, and control complex systems, and it undoubtedly can contribute to the science of risk.
|Item Type:||Journal Article|
|Keywords:||risk; management; complexity; complex systems; hypernetworks; Type-1 dynamics; Type-2 dynamics; multilevel systems; backcloth; traffic; chaos; cellular automata; multi-agent systems; computer simulation;|
|Academic Unit/School:||Faculty of Science, Technology, Engineering and Mathematics (STEM) > Engineering and Innovation
Faculty of Science, Technology, Engineering and Mathematics (STEM)
|Interdisciplinary Research Centre:||Centre for Policing Research and Learning (CPRL)|
|Depositing User:||Jeffrey Johnson|
|Date Deposited:||10 Aug 2007|
|Last Modified:||30 Nov 2016 14:26|
|Share this page:|