Entropy (Feb 2023)

System Integrated Information

  • William Marshall,
  • Matteo Grasso,
  • William G. P. Mayner,
  • Alireza Zaeemzadeh,
  • Leonardo S. Barbosa,
  • Erick Chastain,
  • Graham Findlay,
  • Shuntaro Sasai,
  • Larissa Albantakis,
  • Giulio Tononi

DOI
https://doi.org/10.3390/e25020334
Journal volume & issue
Vol. 25, no. 2
p. 334

Abstract

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Integrated information theory (IIT) starts from consciousness itself and identifies a set of properties (axioms) that are true of every conceivable experience. The axioms are translated into a set of postulates about the substrate of consciousness (called a complex), which are then used to formulate a mathematical framework for assessing both the quality and quantity of experience. The explanatory identity proposed by IIT is that an experience is identical to the cause–effect structure unfolded from a maximally irreducible substrate (a Φ-structure). In this work we introduce a definition for the integrated information of a system (φs) that is based on the existence, intrinsicality, information, and integration postulates of IIT. We explore how notions of determinism, degeneracy, and fault lines in the connectivity impact system-integrated information. We then demonstrate how the proposed measure identifies complexes as systems, the φs of which is greater than the φs of any overlapping candidate systems.

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