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Think complexity : complexity science and computational modeling /
Annotation
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Beijing :
O'Reilly Media,
[2018]
|
| Edición: | Second edition. |
| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
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| 100 | 1 | |a Downey, Allen, |e author. | |
| 245 | 1 | 0 | |a Think complexity : |b complexity science and computational modeling / |c Allen B. Downey. |
| 250 | |a Second edition. | ||
| 264 | 1 | |a Beijing : |b O'Reilly Media, |c [2018] | |
| 264 | 4 | |c ©2018 | |
| 300 | |a 1 online resource | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 588 | 0 | |a Online resource; title from PDF title page (EBSCO, viewed July 16, 2018). | |
| 500 | |a Includes index. | ||
| 505 | 0 | |a Intro; Copyright; Table of Contents; Preface; Who Is This Book For?; Changes from the First Edition; Using the Code; Conventions Used in This Book; O'Reilly Safari; How to Contact Us; Contributor List; Chapter 1. Complexity Science; The Changing Criteria of Science; The Axes of Scientific Models; Different Models for Different Purposes; Complexity Engineering; Complexity Thinking; Chapter 2. Graphs; What Is a Graph?; NetworkX; Random Graphs; Generating Graphs; Connected Graphs; Generating ER Graphs; Probability of Connectivity; Analysis of Graph Algorithms; Exercises | |
| 505 | 8 | |a Chapter 3. Small World GraphsStanley Milgram; Watts and Strogatz; Ring Lattice; WS Graphs; Clustering; Shortest Path Lengths; The WS Experiment; What Kind of Explanation Is That?; Breadth-First Search; Dijkstra's Algorithm; Exercises; Chapter 4. Scale-Free Networks; Social Network Data; WS Model; Degree; Heavy-Tailed Distributions; Barabási-Albert Model; Generating BA Graphs; Cumulative Distributions; Explanatory Models; Exercises; Chapter 5. Cellular Automatons; A Simple CA; Wolfram's Experiment; Classifying CAs; Randomness; Determinism; Spaceships; Universality; Falsifiability | |
| 505 | 8 | |a What Is This a Model Of?Implementing CAs; Cross-Correlation; CA Tables; Exercises; Chapter 6. Game of Life; Conway's GoL; Life Patterns; Conway's Conjecture; Realism; Instrumentalism; Implementing Life; Exercises; Chapter 7. Physical Modeling; Diffusion; Reaction-Diffusion; Percolation; Phase Change; Fractals; Fractals and Percolation Models; Exercises; Chapter 8. Self-Organized Criticality; Critical Systems; Sand Piles; Implementing the Sand Pile; Heavy-Tailed Distributions; Fractals; Pink Noise; The Sound of Sand; Reductionism and Holism; SOC, Causation, and Prediction; Exercises | |
| 505 | 8 | |a Chapter 9. Agent-Based ModelsSchelling's Model; Implementation of Schelling's Model; Segregation; Sugarscape; Wealth Inequality; Implementing Sugarscape; Migration and Wave Behavior; Emergence; Exercises; Chapter 10. Herds, Flocks, and Traffic Jams; Traffic Jams; Random Perturbation; Boids; The Boid Algorithm; Arbitration; Emergence and Free Will; Exercises; Chapter 11. Evolution; Simulating Evolution; Fitness Landscape; Agents; Simulation; No Differentiation; Evidence of Evolution; Differential Survival; Mutation; Speciation; Summary; Exercises; Chapter 12. Evolution of Cooperation | |
| 505 | 8 | |a Prisoner's DilemmaThe Problem of Nice; Prisoner's Dilemma Tournaments; Simulating Evolution of Cooperation; The Tournament; The Simulation; Results; Conclusions; Exercises; Appendix A. Reading List; Index; About the Author; Colophon | |
| 520 | 8 | |a Annotation |b Expand your Python skills by working with data structures and algorithms in a refreshing context--through an eye-opening exploration of complexity science. Whether you're an intermediate-level Python programmer or a student of computational modeling, you'll delve into examples of complex systems through a series of worked examples, exercises, case studies, and easy-to-understand explanations. In this updated second edition, you'll work with graphs, algorithm analysis, scale-free networks, and cellular automata, using advanced features that make Python such a powerful language. Ideal as a text for courses on Python programming and algorithms, Think Complexity will also help self-learners gain valuable experience with topics and ideas they might not encounter otherwise. For every chapter, there are two Jupyter notebooks in the book's software repository: one contains the code from the chapter, explanatory text, and exercises; the other contains the solutions to the exercises. | |
| 504 | |a Includes bibliographical references and index. | ||
| 590 | |a O'Reilly |b O'Reilly Online Learning: Academic/Public Library Edition | ||
| 650 | 0 | |a Python (Computer program language) | |
| 650 | 0 | |a Computational complexity. | |
| 650 | 6 | |a Python (Langage de programmation) | |
| 650 | 6 | |a Complexité de calcul (Informatique) | |
| 650 | 7 | |a COMPUTERS |x Programming Languages |x Python. |2 bisacsh | |
| 650 | 7 | |a Computational complexity |2 fast | |
| 650 | 7 | |a Python (Computer program language) |2 fast | |
| 650 | 7 | |a Computing & information technology. |2 thema | |
| 650 | 7 | |a Web programming. |2 thema | |
| 650 | 7 | |a Programming & scripting languages: general. |2 thema | |
| 650 | 7 | |a Computer programming |x software engineering. |2 thema | |
| 650 | 7 | |a Computers and IT. |2 ukslc | |
| 776 | 0 | 8 | |i Print version: |a Downey, Allen. |t Think complexity. |b Second edition. |d Beijing : O'Reilly Media, [2018] |z 1492040207 |z 9781492040200 |w (OCoLC)1029806258 |
| 856 | 4 | 0 | |u https://learning.oreilly.com/library/view/~/9781492040194/?ar |z Texto completo (Requiere registro previo con correo institucional) |
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