Think Complexity

“Think Complexity” delves into the intricate world of complex systems and emergent phenomena. It explores how simple rules can give rise to complex behaviors, emphasizing the study of networks, dynamics, and computation. The book delves into topics like agent-based modeling, cellular automata, and network theory to provide insights into understanding the complexity of natural and artificial systems. By drawing on examples from various disciplines, “Think Complexity” offers a comprehensive guide to exploring the patterns and structures that emerge from interactions within complex systems.

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Chapter 11 Evolution

Think Complexity

The most important idea in biology, and possibly all of science, is the theory of evolution by natural selection , which claims that new species are created and existing species change due to natural ...

Chapter 8 Self-organized criticality

Think Complexity

In the previous chapter we saw an example of a system with a critical point and we explored one of the common properties of critical systems, fractal geometry. In this chapter, we explore two other pr...

Index

Think Complexity

1/ f noise, 8.6 1-D cellular automaton, 5.1 1/ f noise, 8.1 Anaconda, 0.3 , 10.3 Appel, Kenneth, 1.2 Aristotelian logic, 1.5 Axelrod, Robert, 12.3 Axtell, Robert, 9.4 abstract model, 1 , 3.8 , 4.8 , 5...

Chapter 12 Evolution of cooperation

Think Complexity

In this final chapter, I take on two questions, one from biology and one from philosophy: In biology, the “problem of altruism" is the apparent conflict between natural selection, which suggests that ...

Chapter 6 Game of Life

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In this chapter we consider two-dimensional cellular automatons, especially John Conway’s Game of Life (GoL). Like some of the 1-D CAs in the previous chapter, GoL follows simple rules and produces su...

Chapter 7 Physical modeling

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The cellular automatons we have seen so far are not physical models; that is, they are not intended to describe systems in the real world. But some CAs are intended as physical models. In this chapter...

Appendix A Reading list

Think Complexity

The following are selected books related to topics in this book. Most are written for a non-technical audience. Axelrod, Robert, Complexity of Cooperation , Princeton University Press, 1997. Axelrod, ...

Chapter 4 Scale-free networks

Think Complexity

In this chapter, we’ll work with data from an online social network, and use a Watts-Strogatz graph to model it. The WS model has characteristics of a small world network, like the data, but it has lo...

Chapter 10 Herds, Flocks, and Traffic Jams

Think Complexity

The agent-based models in the previous chapter are based on grids: the agents occupy discrete locations in two-dimensional space. In this chapter we consider agents that move is continuous space, incl...

Chapter 5 Cellular Automatons

Think Complexity

A cellular automaton (CA) is a model of a world with very simple physics. “Cellular” means that the world is divided into discrete chunks, called cells. An “automaton” is a machine that performs compu...

Chapter 3 Small World Graphs

Think Complexity

Many networks in the real world, including social networks, have the “small world property”, which is that the average distance between nodes, measured in number of edges on the shortest path, is much...

Chapter 1 Complexity Science

Think Complexity

Complexity science is relatively new; it became recognizable as a field, and was given a name, in the 1980s. But its newness is not because it applies the tools of science to a new subject, but becaus...