Introduction

The scope of life models and simulations is as broad as that of biology. It encompasses studies on cell metabolism, intercellular communication, immunology, physiology, development, cognitive processes, molecular evolution, population genetics, epidemiology etc. However, for the purpose of the present book, we will focus on the use of computing and simulation approaches as tools for studying the origins of life. Under the global denomination of ‘automata’, a large number of different frameworks have been used to implement and test models accounting for the emergence of life.

Despite their diversity, these approaches call upon the same fundamental grounding: bottom-up model building. Instead of identifying state variables of the whole system and formulating their relationships by equations, the idea is to start with elementary components and then specify how they interact with one another and with the environment. The whole system behaviour is therefore not an a priori descriptor of the model, but rather emerges from within the system. This kind of reasoning is obviously appropriate for research on the origins of life, where the main question is precisely to find out how a property (life) which is valid for the system (a living being) has emerged out of multiple elements (chemical components), which are not individually endowed with this property.