Towards an extended taxonomy of information dynamics via Integrated Information Decomposition
Pedro A.M. Mediano, Fernando E. Rosas, Andrea I Luppi, Robin L., Carhart-Harris, Daniel Bor, Anil K. Seth, Adam B. Barrett

TL;DR
This paper introduces Integrated Information Decomposition ($$ID), a new framework combining Information Decomposition and Integrated Information theories to better understand and quantify complex multivariate systems' information dynamics.
Contribution
It presents $$ID as a novel, comprehensive framework that uncovers new modes of collective information flow and extends traditional measures of information transfer and complexity.
Findings
Reveals previously unreported modes of collective information flow
Expresses measures of information transfer as aggregates of new modes
Demonstrates extended explanatory power beyond causal discovery methods
Abstract
Complex systems, from the human brain to the global economy, are made of multiple elements that interact in such ways that the behaviour of the `whole' often seems to be more than what is readily explainable in terms of the `sum of the parts.' Our ability to understand and control these systems remains limited, one reason being that we still don't know how best to describe -- and quantify -- the higher-order dynamical interactions that characterise their complexity. To address this limitation, we combine principles from the theories of Information Decomposition and Integrated Information into what we call Integrated Information Decomposition, or ID. ID provides a comprehensive framework to reason about, evaluate, and understand the information dynamics of complex multivariate systems. ID reveals the existence of previously unreported modes of collective information…
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Taxonomy
TopicsComplex Systems and Time Series Analysis · Statistical Mechanics and Entropy · Complex Network Analysis Techniques
