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Complexity Science: The Study of Emergence [Kietas viršelis]

3.60/5 (9 ratings by Goodreads)
(Imperial College London)
  • Formatas: Hardback, 458 pages, aukštis x plotis x storis: 260x182x25 mm, weight: 1120 g, Worked examples or Exercises
  • Išleidimo metai: 17-Nov-2022
  • Leidėjas: Cambridge University Press
  • ISBN-10: 1108834760
  • ISBN-13: 9781108834766
Kitos knygos pagal šią temą:
Complexity Science: The Study of EmergenceDidesnis paveikslėlis
  • Formatas: Hardback, 458 pages, aukštis x plotis x storis: 260x182x25 mm, weight: 1120 g, Worked examples or Exercises
  • Išleidimo metai: 17-Nov-2022
  • Leidėjas: Cambridge University Press
  • ISBN-10: 1108834760
  • ISBN-13: 9781108834766
Kitos knygos pagal šią temą:
Pastovi nuoroda: https://www.kriso.lt/db/9781108834766.html
Raktažodžiai:
"Ecosystems, the human brain, ant colonies, and economic networks are all complex systems displaying collective behaviour, or emergence, beyond the sum of their parts. Complexity science is the systematic investigation of these emergent phenomena, and stretches across disciplines, from physics and mathematics, to biological and social sciences. This introductory textbook provides detailed coverage of this rapidly growing field, accommodating readers from a variety of backgrounds, and with varying levels of mathematical skill. Part I presents the underlying principles of complexity science, to ensure students have a solid understanding of the conceptual framework. The second part introduces the key mathematical tools central to complexity science, gradually developing the mathematical formalism, with more advanced material provided in boxes. A broad range of end of chapter problems and extended projects offer opportunities for homework assignments and student research projects, with solutions available toinstructors online. Key terms are highlighted in bold and listed in a glossary for easy reference, while annotated reading lists offer the option for extended reading and research"--

Recenzijos

'Henrik Jensen has produced a masterpiece - describing complexity science from the perspective of a universal theory applicable to many different subject areas, and based on fundamental theoretical principles. A clear virtue of the exposition is that many different topics relevant for complex systems are first treated in an easy-going introductory way, while concrete mathematical models and applications are then provided in the second part of the book. This is a well-thought-through textbook that presents complexity science as a whole, rather than as a collection of single topics.' Christian Beck, Queen Mary University of London

Daugiau informacijos

This introductory textbook provides detailed coverage of the rapidly growing field of complexity science, for a broad audience of readers.
Acknowledgements xi
Nomenclature xiii
Preface xvii
I Conceptual Foundation of Complexity Science
1(86)
Introduction to Part I
3(2)
1 The Science of Emergence
5(16)
1.1 The Importance of Interaction
9(6)
1.2 Past Views on Emergence
15(3)
1.3 Further Reading
18(1)
1.4 Exercises and Projects
19(2)
2 Conceptual Framework of Emergence
21(25)
2.1 Emergence of a Characteristic Scale or Lack of Scale
23(3)
2.2 Emergence of Collective Robust Degrees of Freedom
26(2)
2.3 Structural Coherence
28(3)
2.4 Evolutionary Diffusion
31(2)
2.5 Breaking of Symmetry
33(2)
2.6 Emergence of Networks
35(2)
2.7 Temporal Mode
37(2)
2.8 Adaptive and Evolutionary Dynamics
39(1)
2.9 Further Reading
40(1)
2.10 Exercises and Projects
41(5)
3 Specific Types of Emergent Behaviour
46(29)
3.1 Ising-Type Models: Transitions and Criticality
48(4)
3.2 Network Models and Scale vs. No Scale
52(5)
3.3 Emergence of Coherence in Time: Synchronisation
57(3)
3.4 Evolutionary Dynamics: Adaptation
60(4)
3.5 Mean-Field Modelling: Dimensionality and Forecasting
64(5)
3.6 Further Reading
69(1)
3.7 Exercises and Projects
70(5)
4 The Value of Prototypical Models of Emergence
75(12)
4.1 The Need for Simplification of Models
76(2)
4.2 O'Keeffe--Einstein Propositions at Work
78(4)
4.3 Further Reading
82(1)
4.4 Exercises and Projects
83(4)
II Mathematical Tools of Complexity Science
87(314)
Introduction to Part II
89(4)
5 Branching Processes
93(17)
5.1 Generator Functions: Sizes and Lifetimes
97(6)
5.1.1 Size of the Progeny
99(3)
5.1.2 Time to Extinction
102(1)
5.2 Branching Trees and Random Walks
103(3)
5.3 Further Reading
106(1)
5.4 Exercises and Projects
107(3)
6 Statistical Mechanics
110(53)
6.1 Probabilities and Ensembles
110(9)
6.2 The Ising Model
119(6)
6.3 The Peculiar Nature of the Critical Point
125(2)
6.4 Fluctuations, Response and Correlations
127(5)
6.5 Examples of Correlation Functions: Brain, Flocks of Birds, Finance
132(1)
6.6 Diverging Range of Correlations
133(10)
6.6.1 Correlation Function -- Exact Approach
134(5)
6.6.2 Correlation Function -- Intuitive Discussion
139(4)
6.7 The Two-Dimensional XY Model
143(13)
6.7.1 2d XY: Some Mathematical Details
148(5)
6.7.2 Vortex Unbinding
153(1)
6.7.3 The Vortex Unbinding Transition in Other Systems
154(2)
6.8 Further Reading
156(1)
6.9 Exercises and Projects
156(7)
7 Synchronisation
163(14)
7.1 The Kuramoto Model: The Onset of Synchronisation
164(6)
7.2 Chimera States
170(4)
7.3 Further Reading
174(1)
7.4 Exercises and Projects
175(2)
8 Network Theory
177(53)
8.1 Basic Concepts
178(1)
8.2 Measures of the Importance of Nodes
179(9)
8.2.1 Degree Centrality
179(5)
8.2.2 Eigenvector Centrality
184(3)
8.2.3 Closeness Centrality
187(1)
8.2.4 Betweenness Centrality
187(1)
8.2.5 How Well Does it Work?
188(1)
8.3 Community Detection
188(8)
8.4 Spreading on Networks -- Giant Cluster
196(7)
8.5 Analysis of Dynamics of and on Networks
203(21)
8.5.1 Generating Networks
204(8)
8.5.2 Random Walk on Networks
212(4)
8.5.3 Synchronisation on Networks
216(8)
8.6 Further Reading
224(1)
8.7 Exercises and Projects
225(5)
9 Information Theory and Entropy
230(49)
9.1 Information Theory and Interdependence
232(5)
9.2 Entropy and Estimates of Causal Relations
237(4)
9.3 From Time Series to Networks
241(4)
9.4 From Entropy to Probability Distribution
245(11)
9.5 Measures of Degrees of Complexity
256(18)
9.5.1 Lempel--Ziv Complexity Measure
256(3)
9.5.2 Information-Theoretic Approach to Emergence
259(13)
9.5.3 Group Entropy Measure of Complexity
272(2)
9.6 Further Reading
274(1)
9.7 Exercises and Projects
275(4)
10 Stochastic Dynamics and Equations for the Probabilities
279(45)
10.1 Random Walk and Diffusion
280(13)
10.2 First Passage and First Return Times
293(4)
10.3 Correlations in Time
297(5)
10.4 Random Walk with Persistence or Anti-persistence: Hurst Exponent
302(5)
10.5 Stationary Diffusion: Ornstein--Uhlenbeck Process
307(2)
10.6 Evolutionary Dynamics and Clustering
309(4)
10.7 Master Equation, Coarse Graining and Free Energy
313(5)
10.8 Further Reading
318(1)
10.9 Exercises and Projects
319(5)
11 Agent-Based Modelling
324(32)
11.1 Flocks of Birds or Schools of Fish
325(3)
11.2 Models of Segregation
328(9)
11.3 The Tangled Nature Model
337(12)
11.4 Further Reading
349(1)
11.5 Exercises and Projects
350(6)
12 Intermittency
356(31)
12.1 Self-Organised Criticality
357(13)
12.1.1 Sandpile Models
358(3)
12.1.2 Mean-Field Analysis
361(3)
12.1.3 Lessons from Sandpile Models
364(3)
12.1.4 Forest Fire Model
367(3)
12.2 Record Dynamics
370(9)
12.2.1 Statistics of Records
371(4)
12.2.2 Spin Glasses, Superconductors, Ants and Evolution
375(4)
12.3 Tangent Map Intermittency
379(3)
12.4 Further Reading
382(1)
12.5 Exercises and Projects
383(4)
13 Tipping Points, Transitions and Forecasting
387(10)
13.1 Externally Induced Transitions
387(2)
13.2 Intrinsic Instability
389(6)
13.3 Further Reading
395(1)
13.4 Exercises and Projects
395(2)
14 Concluding Comments and a Look to the Future
397(4)
14.1 Further Reading
399(2)
Glossary 401(10)
References 411(25)
Index 436
Henrik Jeldtoft Jensen is Professor of Mathematical Physics at Imperial College London, and leads the Centre for Complexity Science. He is a prominent expert in complexity science and is involved in a variety of high-profile research projects including the application of co-evolutionary dynamics to the modelling of socio-economical sustainability, finance, cultural evolution, innovation, and cell diversity in cancer tumour growth, and has also worked with the Guildhall School of Music and Drama to identify differences in the neuronal response of audience and performers depending on the mode of performance. He has published two books on self-organized criticality and complex systems.