Towards a unified taxonomy of information dynamics via Integrated Information Decomposition

Abstract

Our ability to understand and control complex systems of many interacting parts remains limited. A key challenge is that we still don’t know how best to describe – and quantify – the many-to-many dynamical interactions that characterise their complexity. To address this limitation, we introduce the mathematical framework of Integrated Information Decomposition, or ΦID. ΦID provides a comprehensive framework to disentangle and characterise the information dynamics of complex multivariate systems. On the theoretical side, ΦID reveals the existence of previously unreported modes of collective information flow, providing tools to express well-known measures of information transfer, information storage, and dynamical complexity as aggregates of these modes, thereby overcoming some of their known theoretical shortcomings. On the empirical side, we validate our theoretical results with computational models and examples from over 1,000 biological, social, physical, and synthetic dynamical systems. Altogether, ΦID improves our understanding of the behaviour of widely-used measures for characterising complex systems across disciplines, and leads to new more refined analyses of dynamical complexity