On Complexity

• Assignments

• 1. Preface
  • 1.1. Introduction
  • 1.2. Prerequisites
  • 1.3. Changes from the Second Edition of Think Complexity
  • 1.4. Changes from the First Edition of Think Complexity
  • 1.5. Running the Code
• 2. Complexity Science
  • 2.1. Introduction
  • 2.2. The Changing Criteria of Science
  • 2.3. The Axes of Scientific Models
  • 2.4. Different Models for Different Purposes
  • 2.5. Complexity Engineering
  • 2.6. Complexity Thinking
  • 2.7. Glossary
  • 2.8. Matching
• 3. Algorithm Analysis
  • 3.1. What Is Algorithm Analysis?
    • 3.1.1. Some Needed Math Notation
    • 3.1.2. Applying the Math Notation
  • 3.2. Big-O Notation
  • 3.3. Algorithm Analysis Examples
    • 3.3.1. An Anagram Detection Example
    • 3.3.2. The Traveling Salesperson Problem
  • 3.4. Glossary
  • 3.5. Matching
• 4. Graphs
  • 4.1. Introduction
  • 4.2. What is a Graph?
  • 4.3. NetworkX
  • 4.4. Random Graphs
  • 4.5. Generating Graphs
  • 4.6. Connected Graphs
  • 4.7. Generating ER Graphs
  • 4.8. Probability of Connectivity
  • 4.9. Analysis of Graph Algorithms
  • 4.10. Exercises
  • 4.11. Glossary
  • 4.12. Matching
  • 4.13. Self Check
• 5. Small World Graphs
  • 5.1. Introduction
  • 5.2. Stanley Milgram
  • 5.3. Watts and Strogatz
  • 5.4. Ring lattice
  • 5.5. WS Graphs
  • 5.6. Clustering
  • 5.7. Shortest Path Lengths
  • 5.8. The WS Experiment
  • 5.9. What Kind of Explanation is that?
  • 5.10. Breadth-First Search
  • 5.11. Dijkstra’s Algorithm
  • 5.12. Exercises
  • 5.13. Glossary
  • 5.14. Matching
  • 5.15. Self Check
• 6. Scale-Free Networks
  • 6.1. Introduction
  • 6.2. Social Network Data
  • 6.3. WS Models
  • 6.4. Degree
  • 6.5. Heavy-tailed Distributions
  • 6.6. Barabási-Albert Model
  • 6.7. Generating BA Graphs
  • 6.8. Cumulative Distributions
  • 6.9. Explanatory Models
  • 6.10. Exercises
  • 6.11. Glossary
  • 6.12. Matching
  • 6.13. Self Check
• 7. Cellular Automatons
  • 7.1. Introduction
  • 7.2. A Simple CA
  • 7.3. Wolfram’s Experiment
  • 7.4. Classifying CAs
  • 7.5. Randomness
  • 7.6. Determinism
  • 7.7. Spaceships
  • 7.8. Universality
  • 7.9. Falsifiability
  • 7.10. What is this a Model of?
  • 7.11. Implementing CAs
  • 7.12. Cross-Correlation
  • 7.13. CA Tables
  • 7.14. Exercises
  • 7.15. Glossary
  • 7.16. Matching
  • 7.17. Self Check
• 8. Game of Life
  • 8.1. Introduction
  • 8.2. Conway’s GoL
  • 8.3. Life Pattern
  • 8.4. Conway’s Conjecture
  • 8.5. Realism
  • 8.6. Instrumentalism
  • 8.7. Implementing Life
  • 8.8. Exercises
  • 8.9. Glossary
  • 8.10. Matching
  • 8.11. Self Check
• 9. Physical Modeling
  • 9.1. Introduction
  • 9.2. Diffusion
  • 9.3. Reaction-Diffusion
  • 9.4. Percolation
  • 9.5. Phase Change
  • 9.6. Fractals
  • 9.7. Fractals and Percolation Models
  • 9.8. Exercises
  • 9.9. Glossary
  • 9.10. Matching
  • 9.11. Self Check
• 10. Self-Organized Criticality
  • 10.1. Introduction
  • 10.2. Critical Systems
  • 10.3. Sand Piles
  • 10.4. Implementing the Sand Pile
  • 10.5. Heavy-Tailed Distributions
  • 10.6. Fractals
  • 10.7. Pink Noise
  • 10.8. The Sound of Sand
  • 10.9. Reductionism and Holism
  • 10.10. SOC, Causation, and Prediction
  • 10.11. Exercises
  • 10.12. Glossary
  • 10.13. Matching
  • 10.14. Self Check
• 11. Agent-based Models
  • 11.1. Introduction
  • 11.2. Schelling’s Model
  • 11.3. Implementation of Schelling’s Model
  • 11.4. Segregation
  • 11.5. Sugarscape
  • 11.6. Wealth Inequality
  • 11.7. Implementing Sugarscape
  • 11.8. Migration and Wave Behavior
  • 11.9. Emergence
  • 11.10. Exercises
  • 11.11. Glossary
  • 11.12. Matching
  • 11.13. Self Check
• 12. Herds, Flocks, and Traffic Jams
  • 12.1. Introduction
  • 12.2. Traffic Jams
  • 12.3. Random Perturbation
  • 12.4. Boids
  • 12.5. The Boid Algorithm
  • 12.6. Arbitration
  • 12.7. Emergence and Free Will
  • 12.8. Exercises
  • 12.9. Glossary
  • 12.10. Matching
  • 12.11. Self Check
• 13. Evolution
  • 13.1. Introduction
  • 13.2. Simulating Evolution
  • 13.3. Fitness Landscape
  • 13.4. Agents
  • 13.5. Simulation
  • 13.6. No Differentiation
  • 13.7. Evidence of Evolution
  • 13.8. Differential Survival
  • 13.9. Mutation
  • 13.10. Speciation
  • 13.11. Summary
  • 13.12. Exercises
  • 13.13. Glossary
  • 13.14. Matching
  • 13.15. Self Check
• 14. Evolution of Cooperation
  • 14.1. Introduction
  • 14.2. Prisoner’s Dilemma
  • 14.3. The Problem of Nice
  • 14.4. Prisoner’s Dilemma Tournaments
  • 14.5. Simulating Evolution of Cooperation
  • 14.6. The Tournament
  • 14.7. The Simulation
  • 14.8. Results
  • 14.9. Conclusions
  • 14.10. Exercises
  • 14.11. Glossary
  • 14.12. Matching
  • 14.13. Self Check
• 15. Appendix 1
  • 15.1. Installing Juypter Notebooks through Anaconda
• 16. Appendix 2
  • 16.1. Getting Started With Google Colab
  • 16.2. Tips and Tricks

Acknowledgements

We are very grateful to Allen B. Downey for his work in writing Think Complexity and for releasing it under the Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0) which forms the core of this interactive book. The chapter on Algorithm Analysis was ported from one by Jan Pearce, Brad Miller, and David Ranum for the Problem Solving with Algorithms and Data Structures using C++ which was also released under the Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0)

Indices and tables

• Index

• Module Index

• Search Page

On Complexity by Janice L. Pearce is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

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