Passive and Driven Trends in the Evolution of Complexity

TL;DR

This paper investigates whether evolutionary increases in complexity are driven or passive, using artificial life simulations to analyze the conditions under which complexity evolves or stabilizes.

Contribution

It introduces a new technique to distinguish driven from passive complexity trends and demonstrates that evolution can both increase and stabilize complexity depending on conditions.

Findings

Evolution can drive complexity increases in some circumstances.

Complexity can also remain stable through evolution.

The evolution of complexity may be entirely driven but not unidirectional.

Abstract

The nature and source of evolutionary trends in complexity is difficult to assess from the fossil record, and the driven vs. passive nature of such trends has been debated for decades. There are also questions about how effectively artificial life software can evolve increasing levels of complexity. We extend our previous work demonstrating an evolutionary increase in an information theoretic measure of neural complexity in an artificial life system (Polyworld), and introduce a new technique for distinguishing driven from passive trends in complexity. Our experiments show that evolution can and does select for complexity increases in a driven fashion, in some circumstances, but under other conditions it can also select for complexity stability. It is suggested that the evolution of complexity is entirely driven---just not in a single direction---at the scale of species. This leaves open the question of evolutionary trends at larger scales.