of functional aspects of spacetime at multiple scales, which offers an alternative to Robin Milner's theory of bigraphs. Configuration In 1993, Burgess introduced the software CFEngine based in intuitions and practice, focusing on the idea of repeatable desired end-state 'convergence', to manage system configuration. The term convergence, used by Burgess, is now often inaccurately just called idempotence, as convergence in his meaning implied both desired end-state and idempotence of an error correction operator at the desired end-state. Shifting interest from Theoretical Physics to Computer Science, Burgess then began to explore the ad hoc choices initially made, and set out to find a scientific method for understanding such choices in computing systems. Computer immunology, anomaly detection, and machine learning Following a position paper 'manifesto' pointing out the research challenges needed to make self-repairing systems, Burgess undertook to study computer systems as a number of empirical phenomena, taking an approach based on physics to learn first about the scales and patterns. The idea of self-healing, or self-maintaining systems was originally referred to as Computer Immunology, as it was inspired by research into the Danger model of human immune systems. The empirical studies were published in various formats between 1999 and 2003, culminating in a journal summary review, and a more practical method for automated machine learning of system behavioural characters. This incorporated the idea of so-called exponential smoothing (which was called a geometric average) for fast learning, along with a two-dimensional, cylindrical time model which was based on the result that network client-server traffic would be expected to behave like a quasi-periodic stochastic function (a characteristic of a system driven close to equilibrium). The notion of an equilibrium or steady state operation thus became the baseline, replacing arbitrary thresholds used in the monitoring software of the day. The software CFEngine became the proof of concept platform using these methods for system state anomaly detection, from 2002 to the present, and received widespread use. Theoretical models Based on these fundamental empirical studies, Burgess argued for two kinds of theoretical model to describe systems, which he called type 1 and type 2. Type 1 models were dynamical performance models that described machines as changing phenomena. Type 2 were semantic models, concerning the efficacy and influence of human decisions on behaviour, called policy, or desired-state computing. He later developed these further and made connection with Claude Shannon's work on error correction in a paper discussing