Emergence in artificial life

TL;DR

This paper explores the concept of emergence in complex systems and artificial life, proposing an information-based framework to better understand how emergent properties relate to life and self-organization.

Contribution

It introduces an information-centric perspective on emergence, defining it as information appearing at one scale but not another, to aid understanding of life and complexity in artificial and biological systems.

Findings

Emergence can be understood as information appearing at different scales.

An information framework helps avoid materialist limitations in studying emergence.

This approach links emergence to self-organization and complexity.

Abstract

Even when concepts similar to emergence have been used since antiquity, we lack an agreed definition. However, emergence has been identified as one of the main features of complex systems. Most would agree on the statement ``life is complex''. Thus, understanding emergence and complexity should benefit the study of living systems. It can be said that life emerges from the interactions of complex molecules. But how useful is this to understand living systems? Artificial life (ALife) has been developed in recent decades to study life using a synthetic approach: build it to understand it. ALife systems are not so complex, be them soft (simulations), hard (robots), or wet (protocells). Then, we can aim at first understanding emergence in ALife, for then using this knowledge in biology. I argue that to understand emergence and life, it becomes useful to use information as a framework. In a general sense, I define emergence as information that is not present at one scale but is present at another scale. This perspective avoids problems of studying emergence from a materialist framework, and can be also useful in the study of self-organization and complexity.