The Information Theory of Individuality

TL;DR

This paper introduces an information theoretic framework to identify biological individuals as ongoing, bounded information processing units, enabling detection of evolved individuals without assuming their existence beforehand.

Contribution

It proposes an algorithmic method to detect and define individuals based on information propagation, expanding the scope of biological and adaptive phenomena analysis.

Findings

Individuals are characterized by their ability to propagate information over time.

The method detects evolved individuals without prior assumptions.

Applicable across molecular to social scales.

Abstract

We consider biological individuality in terms of information theoretic and graphical principles. Our purpose is to extract through an algorithmic decomposition system-environment boundaries supporting individuality. We infer or detect evolved individuals rather than assume that they exist. Given a set of consistent measurements over time, we discover a coarse-grained or quantized description on a system, inducing partitions (which can be nested). Legitimate individual partitions will propagate information from the past into the future, whereas spurious aggregations will not. Individuals are therefore defined in terms of ongoing, bounded information processing units rather than lists of static features or conventional replication-based definitions which tend to fail in the case of cultural change. One virtue of this approach is that it could expand the scope of what we consider adaptive or biological phenomena, particularly in the microscopic and macroscopic regimes of molecular and social phenomena.