Complexity Explained

by Erdi, Peter

• ISBN13: 9783540357773
• ISBN10: 3540357777
• Format: Hardcover
• Copyright: 2007-12-30
• Publisher: Springer Nature

Summary

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?

Table of Contents

Complex Systems: The Intellectual Landscape	p. 1
The Century of Complexity?	p. 1
Characteristics of Simple and Complex Systems	p. 5
System and Its Environment	p. 5
Simple Systems	p. 6
Complex Systems	p. 7
Connecting the Dots	p. 20
History of Complex Systems Research	p. 25
Reductionist Success Stories Versus the Importance of Organization Principles	p. 25
Reductionism and Holism in Quantum Physics	p. 25
Reductionism and Complexity in Molecular Biology	p. 29
Ancestors of present day complex system research	p. 35
Systems Theory	p. 35
Cybernetics	p. 37
Nonlinear Science in Action: Theory of Dissipative Structures, Synergetics and Catastrophe Theory	p. 45
From the Clockwork World View to Irreversibility (and Back?)	p. 57
Cyclic Universe Versus Linear Time Concept: the Metaphysical Perspective	p. 57
Cyclic Universe	p. 57
Linear Time Concepts	p. 59
The Newtonian Clockwork Universe	p. 61
The Mechanical Clock	p. 61
Kepler's Integral Laws	p. 66
Newton's Differential Laws, Hamilton Equations, Conservative Oscillation, Dissipation	p. 68
Mechanics Versus Thermodynamics	p. 75
Heat Conduction and Irreversibility	p. 75
Steam Engine, Feedback control, Irreversibility	p. 77
The First and Second Laws of Thermodynamics	p. 77
The Birth of the Modern Theory of Dynamical Systems	p. 79
Oscillations	p. 81
The Lotka-Volterra Model	p. 81
Stable Oscillation: Limit Cycles	p. 83
Quasiperiodic Motions: A Few Words About the Modern Theory of Dynamical Systems	p. 86
The Chaos Paradigm: Then and Now	p. 87
Defining and Detecting Chaos	p. 87
Structural and Geometrical Conditions of Chaos: what Is Important and What Is Not?	p. 91
The Necessity of Being Chaotic	p. 94
Controlling Chaos: Why and How?	p. 96
Traveling to High-Dimension Land: Chaotic Itinerancy	p. 98
Direction of Evolution	p. 100
Dollo's Law in Retrospective	p. 100
Is Something Never-Decreasing During Evolution?	p. 102
Cyclic Universe: Revisited...and Criticized	p. 105
The Dynamic World View in Action	p. 109
Causality, Teleology and About the Scope and Limits of the Dynamical Paradigm	p. 109
Causal Versus Teleological Description	p. 110
Causality, Networks, Emergent Novelty	p. 112
Chemical Kinetics: A Prototype of Nonlinear Science	p. 113
On the Structure - Dynamics Relationship for Chemical Reactions	p. 118
Chemical Kinetics as a Metalanguage	p. 119
Spatiotemporal Patterns in Chemistry and Biology	p. 120
Systems Biology: The Half Admitted Renaissance of Cybernetics and Systems Theory	p. 130
Life itself	p. 130
Cells As Self-Referential Systems	p. 131
The Old-New Systems Biology	p. 133
Random Boolean Networks: Model Framework and Applications for Genetic Networks	p. 135
Population Dynamic and Epidemic Models: Biological and Social	p. 140
Connectivity, Stability, Diversity	p. 140
The Epidemic Propagation of Infections and Ideas	p. 144
Modeling Social Epidemics	p. 146
Evolutionary Dynamics	p. 147
Dynamic Models of War and Love	p. 148
Lanchaster's Combat Model and Its Variations	p. 148
Is Love Different from War?	p. 151
Social Dynamics: Some Examples	p. 154
Segregation dynamics	p. 154
Opinion Dynamics	p. 157
Nonlinear Dynamics in Economics: Some Examples	p. 159
Business Cycles	p. 159
Controlling Chaos in Economic Models	p. 161
Drug Market: Controlling Chaos	p. 162
The Search for Laws: Deductive Versus Inductive	p. 165
Deductive Versus Inductive Arguments	p. 165
Principia Mathematica and the Deductive Approach: From Newton to Russell and Whitehead	p. 167
Karl Popper and the Problem of Induction	p. 169
Cybernetics: Bridge Between Natural and Artificial	p. 169
John von Neumann: The Real Pioneer of Complex Systems Studies	p. 170
Artificial Intelligence, Herbert Simon and the Bounded Rationality	p. 175
Inductive Reasoning and Bounded Rationality: from Herbert Simon to Brian Arthur	p. 178
Minority Game	p. 180
Summary and "What Next?"	p. 182
Statistical Laws: From Symmetric to Asymmetric	p. 185
Normal Distribution	p. 185
General Remarks	p. 185
Generation of Normal Distribution: Brownian Motion	p. 187
Liouville Process, Wiener and Special Wiener Process, Ornstein-Uhlenbeck Process	p. 188
Bimodal and Multimodal Distributions	p. 190
Long Tail Distributions	p. 191
Lognormal and Power Law Distributions: Phenomenology	p. 191
Generation of Lognormal and Power Law Distributions	p. 194
Simple and Complex Structures: Between Order and Randomness	p. 201
Complexity and Randomness	p. 201
Structural Complexity	p. 203
Structures and Graphs	p. 204
Complexity of Graphs	p. 208
Fractal Structures	p. 212
Noise-Induced Ordering: An Elementary Mathematical Model	p. 217
Networks Everywhere: Between Order and Randomness	p. 219
Statistical Approach to Large Networks	p. 219
Networks in Cell Biology	p. 221
Epidemics on Networks	p. 223
Citation and Collaboration Networks in Science and Technology	p. 225
Complexity of the Brain: Structure, Function and Dynamics	p. 237
Introductory Remarks	p. 237
Windows on the Brain	p. 238
A Few Words About the Brain-Mind Problem	p. 238
Experimental Methods: A Brief Review	p. 239
Approaches and Organizational Principles	p. 241
Levels	p. 241
Bottom Up and top Down	p. 242
Organizational Principles	p. 243
Single Cells	p. 247
Single Cells: General Remarks	p. 247
Single Cell Modeling: Deterministic and Stochastic Framework	p. 250
Structure, Dynamics, Function	p. 255
Structural Aspects	p. 255
Neural Rhythms	p. 261
Variations on the Hebbian Learning Rule: Different Roots	p. 283
Complexity and Cybernetics: Towards a Unified Theory of Brain-Mind and Computer	p. 289
Cybernetics Strikes Back	p. 289
From Cognitive Science to Embodied Cognition	p. 291
The Brain as a Hermeneutic Device	p. 296
From Neurons to Soul and Back	p. 299
From Models to Decision Making	p. 305
Equation-Based Versus Agent-Based Model	p. 305
Motivations	p. 305
Artificial Life	p. 306
Artificial Societies	p. 311
Agent-Based Computational Economics	p. 316
Game Theory: Where We Are Now?	p. 318
Classical game theory	p. 318
Evolutionary Game Theory	p. 322
Widening the Limits to Predictions: Earthquake, Eruptions Epileptics Seizures, and Stock Market Crashes	p. 328
Scope and Limits of Predictability	p. 328
Phenomenology	p. 329
Statistical Analysis of Extreme Events	p. 338
Towards Predicting Seizures	p. 341
Towards Predicting Market Crashes: Analysis of Price Peaks	p. 344
Dynamical Models of Extreme Events	p. 345
How Many Cultures We Have?	p. 353
Complexity as a Unifying Concept	p. 353
Systems and Simulations	p. 353
The Topics of the Book in Retrospective: Natural and Human Socioeconomic Systems	p. 354
The Ingredients of Complex Systems	p. 357
Complexity Explained: In Defense of (Bounded) Rationality	p. 359
References	p. 365
Index	p. 393
Table of Contents provided by Ingram. All Rights Reserved.