As science probes the nature of life, society, and technology ever more closely, what it finds there is complexity. The sophisticated group behavior of social insects, the unexpected intricacies of the genome, the dynamics of population growth, and the self-organized structure of the World Wide Web - these are just a few examples of complex systems that still elude scientific understanding. Comprehending such systems seems to require a wholly new approach, one that goes beyond traditional scientific reductionism and that re-maps long-standing disciplinary boundaries. This remarkably accessible and companionable book, written by a leading complex systems scientist, provides an intimate, detailed tour of the sciences of complexity, a broad set of efforts that seek to explain how large-scale complex, organized, and adaptive behavior can emerge from simple interactions among myriad individuals. In this richly illustrated work, Melanie Mitchell describes in equal parts the history of ideas underlying complex systems science, the current research at the forefront of this field, and the prospects for the field's contribution to solving some of the most important scientific questions of our current century.
Pt. 1 Background and History
Ch. 1 What Is Complexity? 3
Ch. 2 Dynamics, Chaos, and Prediction 15
Ch. 3 Information 40
Ch. 4 Computation 56
Ch. 5 Evolution 71
Ch. 6 Genetics, Simplified 88
Ch. 7 Defining and Measuring Complexity 94
Pt. 2 Life and Evolution in Computers
Ch. 8 Self-Reproducing Computer Programs 115
Ch. 9 Genetic Algorithms 127
Pt. 3 Computation Writ Large
Ch. 10 Cellular Automata, Life, and the Universe 145
Ch. 11 Computing with Particles 160
Ch. 12 Information Processing in Living Systems 169
Ch. 13 How to Make Analogies (if You Are a Computer) 186
Ch. 14 Prospects of Computer Modeling 209
Pt. 4 Network Thinking
Ch. 15 The Science of Networks 227
Ch. 16 Applying Network Science to Real-World Networks 247
Ch. 17 The Mystery of Scaling 258
Ch. 18 Evolution, Complexified 273
Pt. 5 Conclusion
Ch. 19 The Past and Future of the Sciences of Complexity 291
Notes 304
Bibliography 326
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