This book provides a short, hands-on introduction to the science of
complexity using simple computational models of natural complex
systems--with models and exercises drawn from physics, chemistry,
geology, and biology. By working through the models and engaging in
additional computational explorations suggested at the end of each
chapter, readers very quickly develop an understanding of how complex
structures and behaviors can emerge in natural phenomena as diverse as
avalanches, forest fires, earthquakes, chemical reactions, animal
flocks, and epidemic diseases.
Natural Complexity provides the necessary topical background, complete
source codes in Python, and detailed explanations for all computational
models. Ideal for undergraduates, beginning graduate students, and
researchers in the physical and natural sciences, this unique handbook
requires no advanced mathematical knowledge or programming skills and is
suitable for self-learners with a working knowledge of precalculus and
high-school physics.
Self-contained and accessible, Natural Complexity enables readers to
identify and quantify common underlying structural and dynamical
patterns shared by the various systems and phenomena it examines, so
that they can form their own answers to the questions of what natural
complexity is and how it arises.