Note: [] Corresponding author: Hussein A. Abbass, School of Engineering
and Information Technology, University of New South Wales, Australian Defence
Force Academy Campus, Canberra, ACT 2600, Australia. E-mail: [email protected]
Abstract: Causality is grounded in every scientific field. Computational
modelling is no exception, except that it is our focus in this article. But
what if we have made a mistake? Is causality a constraint on our understanding
of complex systems? Is it an obstacle in our ability to build theories to
control change in complex systems? Or do we merely need to refine the concept
as we evolve from one level of complexity to another? We start the journey of this article by glancing over a few key pieces of work from Philosophy and
Metaphysics. We then centre the discussion on the pivotal element of this
paper, causality of change in complex systems of systems and demonstrate that a
counterfactual analysis of causality breaks down. We steer the discussion more
towards "change" and the separation between physical and perceptual elements.
Three applications are presented as examples of the type of complexity we face
in computational modelling of complex systems of systems. These three
applications – covering story generation in linguistics, network centric
operations in defence and interdependency security problems – demonstrate how
causal dependencies can be modelled, identified and extracted from a
computational environment that mimics real-world complex systems of systems. We
conclude the paper with a proposed model to control change in complex systems;
a model we call the E4 model.
