Many of the systems we build are complicated, with lots of moving parts and interactions. We have developed engineering techniques to address these complications (for example layered and nested abstractions) that break-up large systems into smaller component parts that can be developed and reasoned about independently. But an increasing number of engineered systems are complex, and resistant to this kind of decomposition. Complex systems don’t have easily-identified components, and exhibit “emergent” behaviours that self-organise in unexpected ways out of small-scale interactions. Natural systems have always exhibited these properties, of course – and now our artefacts are doing too. Paradoxically this can make systems more predictable, more responsive, more robust, and more stable, using self-organisation to respond to even small changes in the environment in ways that maintain desirable macroscopic behaviour. How can the study complex systems affect the kinds of self-organisation we’re introducing into engineering? In this tutorial we’ll explore how to think about complexity, drawing on insights from physics, biology, mathematics, and computer science. We’ll illustrate the ideas using different networks that exhibit a lot of complex systems features really well, and how simulation can be used to tackle problems for can’t tackle mathematically. And we’ll look forward to new techniques emerging in the literature that we can potentially apply to engineering self-organising systems.

Prerequisites: An interest in the theory of complex systems and how it relates to engineering applications

Simon Dobson is Professor of Computer Science in the School of Computer Science at the University of St Andrews. He was elected Fellow of the Royal Society of Edinburgh, Scotland’s national academy, in 2020, and serves as a science adviser to the Scottish government as a member of the Scottish Science Advisory Council.

Simon works on complex and sensor systems, especially on sensor data analytics and the modelling of epidemic processes over complex networks. His research has generated over 150 internationally peer-reviewed publications, driven by leadership roles in research grants worth over EUR30M – most recently as part of a £5M EPSRC-funded programme grant in the Science of Sensor Systems Software He has served, amongst other activities, on the steering committee of the ACSOS conference; as programme and general chairs for the IEEE International Conference on Autonomic Computing; as an associate editor of ACM Transactions on Autonomous and Adaptive Systems; as a member of UKCRC, the expert committee on UK computing research; as the chair of the BCS Distinguished PhD Dissertations award panel; and on the programme committees of a wide range of leading international conferences and specialised workshops. He was a director and vice-president of the European Research Consortium for Informatics and Mathematics from 2006 – 2009, and has served on a number of national and EU committees and strategic initiatives.

Simon has previously worked at the UK STFC‘s Rutherford Appleton Laboratory; at Trinity College Dublin and UCD Dublin in Ireland; and was also the founder and CEO of Aurium, a research-led Dublin-based start-up company. He holds a BSc from the University of Newcastle upon Tyne and DPhil from the University of York, both in computer science, is a Chartered Engineer and a Fellow of the British Computer Society .