What is included with this book?
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 |
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