Year: 2025
Type: article
Abstract: Learning—in addition to thermodynamic dissipation, autocatalysis and homeostasis—has been hypothesized to be a key pillar of all living systems. Here, we examine the myriad ways in which organisms on Earth learn over various time and length scales—from Darwinian evolution to protein computation to the scientific method—in order to draw abstractions about the process of learning in general. Be it in life on Earth or lyfe elsewhere in the universe, we propose that learning can be characterized by a combination of mechanisms that favour functional fitness and those that favour novelty search. We also propose that feedbacks related to learning and dissipation, learning and environmental complexity and learning and self-modelling may be general features that guide how the information-processing and predictive abilities of learning systems evolve with time, perhaps even at the scale of planetary biospheres.
Source: Interface Focus
Authors: Stuart Bartlett, Michael L. Wong
Language: English
Topic: Complex Systems and Dynamics
Subfield: Statistical and Nonlinear Physics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4417476731