## Complexity Explained (Google eBook)This book explains why complex systems research is important in understanding the structure, function and dynamics of complex natural and social phenomena. It illuminates how complex collective behavior emerges from the parts of a system, due to the interaction between the system and its environment. You will learn the basic concepts and methods of complex system research. It is shown that very different complex phenomena of nature and society can be analyzed and understood by nonlinear dynamics since many systems of very different fields, such as physics, chemistry, biology, economics, psychology and sociology etc. have similar architecture. “Complexity Explained” is not highly technical and mathematical, but teaches and uses the basic mathematical notions of dynamical system theory making the book useful for students of science majors and graduate courses, but it should be readable for a more general audience; actually for those, who ask: What complex systems really are? |

### What people are saying - Write a review

We haven't found any reviews in the usual places.

### Contents

1 | |

5 | |

6 | |

7 | |

13 Connecting the Dots | 20 |

History of Complex Systems Research | 25 |

212 Reductionism and Complexity in Molecular Biology Capsule History of Early Molecular Biology | 29 |

22 Ancestors of present day complex system research | 35 |

56 Artiﬁcial Intelligence Herbert Simon and the Bounded Rationality | 175 |

from Herbert Simon to Brian Arthur | 178 |

58 Minority Game | 180 |

59 Summary and What Next? | 182 |

Statistical Laws From Symmetric to Asymmetric | 185 |

Brownian Motion | 187 |

613 Liouville Process Wiener and Special Wiener Process OrnsteinUhlenbeck Process | 188 |

62 Bimodal and Multimodal Distributions | 190 |

222 Cybernetics | 37 |

Theory of Dissipative Structures Synergetics and Catastrophe Theory | 45 |

From the Clockwork World View to Irreversibility and Back? | 56 |

312 Linear Time Concepts | 59 |

32 The Newtonian Clockwork Universe | 61 |

322 Keplers Integral Laws | 66 |

323 Newtons Differential Laws Hamilton Equations Conservative Oscillation Dissipation | 68 |

33 Mechanics Versus Thermodynamics | 75 |

332 Steam Engine Feedback control Irreversibility | 77 |

34 The Birth of the Modern Theory of Dynamical Systems | 79 |

35 Oscillations | 81 |

Limit Cycles | 83 |

A Few Words About the Modern Theory of Dynamical Systems | 86 |

Then and Now | 87 |

what Is Important and What Is Not? | 91 |

363 The Necessity of Being Chaotic | 94 |

Why and How? | 96 |

Chaotic Itinerancy | 98 |

37 Direction of Evolution | 100 |

372 Is Something NeverDecreasing During Evolution? | 102 |

Revisitedand Criticized | 105 |

The Dynamic World View in Action | 109 |

411 Causal Versus Teleological Description | 110 |

412 Causality Networks Emergent Novelty | 112 |

A Prototype of Nonlinear Science | 113 |

421 On the StructureDynamics Relationship for Chemical Reactions | 118 |

422 Chemical Kinetics as a Metalanguage | 119 |

423 Spatiotemporal Patterns in Chemistry and Biology | 120 |

The Half Admitted Renaissance of Cybernetics and Systems Theory | 130 |

432 Cells As SelfReferential Systems | 131 |

433 The OldNew Systems Biology | 133 |

Model Framework and Applications for Genetic Networks | 135 |

Biological and Social | 140 |

442 The Epidemic Propagation of Infections and Ideas | 144 |

443 Modeling Social Epidemics | 146 |

45 Evolutionary Dynamics | 147 |

46 Dynamic Models of War and Love | 148 |

462 Is Love Different from War? | 151 |

Some Examples | 154 |

472 Opinion Dynamics | 157 |

Some Examples | 159 |

482 Controlling Chaos in Economic Models | 161 |

Controlling Chaos | 162 |

The Search for Laws Deductive Versus Inductive | 164 |

From Newton to Russell and Whitehead | 167 |

53 Karl Popper and the Problem of Induction | 169 |

The Real Pioneer of Complex Systems Studies | 170 |

63 Long Tail Distributions | 191 |

632 Generation of Lognormal and Power Law Distributions | 194 |

Simple and Complex Structures Between Order and Randomness | 200 |

72 Structural Complexity | 203 |

721 Structures and Graphs | 204 |

722 Complexity of Graphs | 208 |

723 Fractal Structures | 212 |

An Elementary Mathematical Model | 217 |

Between Order and Randomness | 219 |

742 Networks in Cell Biology | 221 |

743 Epidemics on Networks | 223 |

744 Citation and Collaboration Networks in Science and Technology | 225 |

Complexity of the Brain Structure Function and Dynamics | 237 |

82 Windows on the Brain | 238 |

A Brief Review | 239 |

83 Approaches and Organizational Principles | 241 |

832 Bottom Up and top Down | 242 |

833 Organizational Principles | 243 |

84 Single Cells | 247 |

Deterministic and Stochastic Framework | 250 |

85 Structure Dynamics Function | 255 |

852 Neural Rhythms | 261 |

Different Roots | 283 |

Towards a Uniﬁed Theory of BrainMind and Computer | 289 |

862 From Cognitive Science to Embodied Cognition Cognitive Science | 291 |

863 The Brain as a Hermeneutic Device | 296 |

864 From Neurons to Soul and Back | 299 |

From Models to Decision Making | 304 |

912 Artiﬁcial Life | 306 |

913 Artiﬁcial Societies | 311 |

914 AgentBased Computational Economics | 316 |

Where We Are Now? | 318 |

922 Evolutionary Game Theory | 322 |

Earthquake Eruptions Epileptics Seizures and Stock Market Crashes | 328 |

932 Phenomenology Earthquake Eruption | 329 |

933 Statistical Analysis of Extreme Events | 338 |

934 Towards Predicting Seizures | 341 |

Analysis of Price Peaks | 344 |

936 Dynamical Models of Extreme Events | 345 |

How Many Cultures We Have? | 353 |

Natural and Human Socioeconomic Systems | 354 |

102 The Ingredients of Complex Systems | 357 |

In Defense of Bounded Rationality | 359 |

365 | |

392 | |

### Common terms and phrases

activity agents algorithm analysis analyzed assumption attractor basic behavior biological brain called catastrophe theory causal cells chaos chaotic characterized chemical chemical kinetics citations clock cognitive complex systems components concept connected cybernetics defined describe deterministic distribution dynamical systems edge effect emergence envy-free equilibrium evolution evolutionary evolutionary game theory explain frequency function gene genetic graph Hebbian learning Herbert Simon implies increase initial integration interaction kinetic limit cycle linear mathematical measure mechanism membrane potential methods molecular molecules motion Neumann neural networks neurons nodes nonlinear organization oscillation parameter patent patterns phase phenomena physics place cell players population positive feedback potential power law predict principle problem properties random reactions result role Sect seizures self-organized self-organized criticality simple social spatial stability stochastic strategies structures studied suggested synaptic Systems Biology systems theory temporal theorem theta tion variables visual Wiener Wiener process

### Popular passages

Page 2 - There once were two watchmakers, named Hora and Tempus, who manufactured very fine watches. Both of them were highly regarded, and the phones in their workshops rang frequently new customers were constantly calling them. However, Hora prospered, while Tempus became poorer and poorer and finally lost his shop. What was the reason? The watches the men made consisted of about 1,000 parts each. Tempus had so constructed his that if he had one partly assembled and had to put it down - to answer the phone,...

Page 2 - The better the customers liked his watches, the more they phoned him, the more difficult it became for him to find enough uninterrupted time to finish a watch. The watches that Hora made were no less complex than those of Tempus. But he had designed them so that he could put together subassemblies of about ten elements each.

Page 2 - The watches that Hora made were no less complex than those of Tempus. But he had designed them so that he could put together subassemblies of about ten elements each. Ten of these subassemblies again, could be put together into a larger subassembly; and a system of ten of the latter subassemblies constituted the whole watch. Hence, when Hora had to put down a partly assembled watch in order to answer the phone, he lost only a small part of his work, and he assembled his watches in only a fraction...

### References to this book

Deregulation, Innovation and Market Liberalization: Electricity Regulation ... L. Lynne Kiesling No preview available - 2008 |