Integrated Information and Autonomy in the Thermodynamic Limit

TL;DR

This paper introduces a measure of integrated information to analyze autonomy and self-organization in large systems, applying it to kinetic Ising models to understand how living systems maintain integration and delineate boundaries.

Contribution

It proposes a novel measure of integration based on perturbation responses, extending integrated information theory to the thermodynamic limit without requiring stationarity.

Findings

Living systems near critical points maximize integration sensitivity.

The measure can delineate agent-environment boundaries.

Agent-environment asymmetries can be characterized by the measure.

Abstract

The concept of autonomy is fundamental for understanding biological organization and the evolutionary transitions of living systems. Understanding how a system constitutes itself as an individual, cohesive, self-organized entity is a fundamental challenge for the understanding of life. However, it is generally a difficult task to determine whether the system or its environment has generated the correlations that allow an observer to trace the boundary of a living system as a coherent unit. Inspired by the framework of integrated information theory, we propose a measure of the level of integration of a system as the response of a system to partitions that introduce perturbations in the interaction between subsystems, without assuming the existence of a stationary distribution. With the goal of characterizing transitions in integrated information in the thermodynamic limit, we apply this measure to kinetic Ising models of infinite size using mean field techniques. Our findings suggest that, in order to preserve the integration of causal influences of a system as it grows in size, a living entity must be poised near critical points maximizing its sensitivity to perturbations in the interaction between subsystems. Moreover, we observe how such a measure is able to delimit an agent and its environment, being able to characterize simple instances of agent-environment asymmetries in which the agent has the ability to modulate its coupling with the environment.