Guided Self-Organisation (GSO)

Self-organisation is the evolution of a system into an organised form in the absence of external influences. It brings many attractive properties to systems such as robustness, adaptability and scalability. Self-organising systems can be found practically everywhere: a heated fluid forms regular convection patterns, neuronal ensembles self-organise into complex spike patterns, insect swarms change shape in response to an approaching predator, and ecosystems develop spatial structures in response to diminishing resources.

The emerging field of guided self-organisation (GSO) explores the possibility of channelling self-organisation within a system in order to achieve a desirable pattern or outcome.

GSO attempts to reconcile two seemingly opposing forces: guiding a self-organising system into a better structured shape and/or functionality, while diversifying the options in an entropic exploration within the available search space. GSO supposes that, rather than trying to precisely control a transition towards the desirable outcomes, you can put in place some constraints on the system dynamics to mediate behaviours and interactions.

We approach GSO by examining the information processing properties of systems. In doing so, we aim to quantify their structure, function, and constraints in a rigorous, system-independent fashion. We use information-theoretic measures of complexity, criticality, and computation (“information dynamics”), including transfer entropy and synergistic information. We also develop cross-disciplinary methods, relating between information theory and thermodynamics (“information thermodynamics”), game theory, as well as complex networks.

Research staff

Honorary Associates at the University of Sydney

Some of our recent selected publications on GSO are included in the repository of The International Association for GSO for which we serve as a central node.

Selected projects: