The Role of Redundancy in the Robustness of Random Boolean Networks

TL;DR

This paper investigates how adding redundant nodes to Random Boolean Networks enhances their robustness and potentially smoothens fitness landscapes, thereby facilitating evolutionary search processes.

Contribution

It demonstrates through simulations that redundancy increases RBN robustness and supports Kauffman's conjecture on the role of redundancy in evolution.

Findings

Redundant nodes improve network robustness

Redundancy may smooth fitness landscapes

Excess redundancy could hinder adaptation

Abstract

Evolution depends on the possibility of successfully exploring fitness landscapes via mutation and recombination. With these search procedures, exploration is difficult in "rugged" fitness landscapes, where small mutations can drastically change functionalities in an organism. Random Boolean networks (RBNs), being general models, can be used to explore theories of how evolution can take place in rugged landscapes; or even change the landscapes. In this paper, we study the effect that redundant nodes have on the robustness of RBNs. Using computer simulations, we have found that the addition of redundant nodes to RBNs increases their robustness. We conjecture that redundancy is a way of "smoothening" fitness landscapes. Therefore, redundancy can facilitate evolutionary searches. However, too much redundancy could reduce the rate of adaptation of an evolutionary process. Our results also provide supporting evidence in favour of Kauffman's conjecture (Kauffman, 2000, p.195).