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And in fact in the course of this chapter , I will construct a whole sequence of remarkably simple models that do rather well at reproducing the main features of complex behavior in a wide range of everyday natural and other systems.
But even using a whole range of tricks suggested by biology—as well as quite a number that are not—I have never been successful.
If one looks at species that exist today, and at the fossil record of past species, then one of the most striking features is just how much is in common across vast ranges of different organisms.
My guess is that as in other situations, its main systematic contribution is to make things simpler, and that insofar as things do end up getting more complicated, this is almost always the result of essentially random
An example of a basic pattern that is produced in several variants by a wide range of simple programs.
But while features such as the shapes of leaves typically differ greatly between different plants, there are also some seemingly quite sophisticated aspects of plants that typically remain almost exactly the same across a huge range of species.
In animals, however, the lack of rigidity allows a vastly wider range of structures to appear, since now tissue in different regions need not just grow uniformly, but can change shape in a whole variety of ways.
And comparing the patterns in these pictures with patterns on actual mollusc shells, one notices the remarkable fact that the range of patterns that occur in the two cases is extremely similar.
Beginning in the 1940s, the development of electronic computers greatly broadened the range of calculations that could be done.
But if one uses three connections, a vast range of networks immediately become possible.
And even after I had seen the first signs of complexity in cellular automata, it was several more years before I discovered the full range of examples given in this chapter , and realized just how easily complexity could be generated in systems like cellular automata.
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