By Paul Charbonneau
Princeton University Press
This book aims to introduce readers to the study of complex systems with the help of simple computational models. After showing how difficult it is to define complexity, the author explains that complex systems are an idealisation of naturally occurring phenomena in which the macroscopic structures and patterns generated are not directly controlled by processes at the macroscopic level but arise instead from dynamical interactions at the microscopic level. This kind of behaviour characterises a range of natural phenomena, from avalanches to earthquakes, solar flares, epidemics and ant colonies.
In each chapter the author introduces a simple computer-based model for one such complex phenomenon. As the author himself states, such simplified models wouldn’t be able to reliably foresee the development of a real natural phenomenon, thus they are to be taken as complementary to conventional approaches for studying such systems.
Meant for undergraduate students, the book does not require previous experience in programming and each computational model is accompanied by Python code and full explanations. Nevertheless, students are expected to learn how to modify the code to tackle the problems included at the end of each chapter. Three appendices provide a review of Python programming, probability density functions and other useful mathematical tools.
