Complexity Science

An Introduction

By: Mark A Peletier, Rutger A Van Santen, Erik Steur

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eText | 20 March 2019

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This book on complexity science comprises a collection of chapters on methods and principles from a wide variety of disciplinary fields — from physics and chemistry to biology and the social sciences.

In this two-part volume, the first part is a collection of chapters introducing different aspects in a coherent fashion, and providing a common basis and the founding principles of the different complexity science approaches; the next provides deeper discussions of the different methods of use in complexity science, with interesting illustrative applications.

The fundamental topics deal with self-organization, pattern formation, forecasting uncertainties, synchronization and revolutionary change, self-adapting and self-correcting systems, and complex networks. Examples are taken from biology, chemistry, engineering, epidemiology, robotics, economics, sociology, and neurology.

Contents:

Basic Concepts:
- The Many Facets of Complexity
- Disguises of Complexity
Tools:
- Complex Dynamics of Deterministic Nonlinear Systems (Erik Steur and Henk Nijmeijer)
- Pattern Formation in Reaction-Diffusion Systems — An Explicit Approach (Arjen Doelman)
- A Primer on Stochastic Processes (Mark A Peletier)
- Random Graphs Models for Complex Networks, and the Brain (Remco van der Hofstad)
- Mesoscale Simulations of Complex Fluids (Johan T Padding)
Applications:
- Biorhythms and the Brain (Jos H T Rohling and Johanna H Meijer)
- Modelling of Collective Motion (Barry W Fitzgerald, Rutger A van Santen and Johan T Padding)
- Path-Integral Representation of Diluted Pedestrian Dynamics (Alessandro Corbetta and Federico Toschi)
- Chemical Reaction Kinetic Perspective with Mesoscopic Nonequilibrium Thermodynamics (Hong Qian)
- Metabolic Pathways and Optimisation (Robert Planqué and Josephus Hulshof)
- Particle-Based Modelling of Flows Through Obstacles (Emilio N M Cirillo, Adrian Muntean and Rutger A van Santen)

Readership: A wide spectrum of graduate students and researchers interested in complexity ranging from mathematical and chemical to biology and social sciences.Complexity;Self-Organization;Pattern Formation;Synchronization;Networks0Key Features:

Provides tutorial introductory chapters; highlighting theories, concepts and methods at bachelor/master level from a unifying perspective
Includes more advanced chapters that provide deep background on the different matters
Explains and illustrates application areas