The Game of Life was introduced by John Conway in 1970, and its immediate popularity quickly gave wings to the then-obscure field of cellular automata. It's a striking demonstration of bafflingly complex patterns and chaos that emerge from a grid of cells, each obeying utterly simple rules.
The idea that such unpredictable behavior could arise from a collection of cells that were, in and of themselves, entirely predictable, was very exciting. Why? Because this flew in the face of every 'common sense' notion about complexity since humans began practicing science. The common sense notion is that complex behavior arises from complex processes. But the Game of Life exhibited complex, unpredictable behavior from very simple, predictable elements! This raised a lot of eyebrows.
It's interesting to consider the implications of cellular automata in the way the universe works. Stephen Wolfram's magnum opus, A New Kind of Science, is an exploration of this idea. If we allow the possibility that the principles at work in cellular automata such as the Game of Life, are fundamental to the way the universe works, at all scales, then it's easy to see how the kind of complexity that exists all around us may have arisen much in the same way that the complex, organic-looking patterns emerge on the Game of Life. This is a neat concept because it means that all kinds of complexity can appear in reality even if the underlying processes are simple and predictable.
The concept of emergence is key to the model. New objects and properties emerge from a lower level of interaction, in such a way that these new objects and properties can't be understood or predicted in terms of the way their lower-level parts interact. Furthermore, these levels of complexity are built on top of one another. This resonates perfectly with the structure of high-level organisms - the organism emerges from the layer of cells, cells emerge from the layer of molecules, molecules from atoms, and so on. There is nothing about the interaction of individual cells in a kangaroo that can be used to predict what that kangaroo will look like (or what it will do next). In other words, phenomena at a certain level can not be reduced to, or explained by, the level underlying it. Reductionism is not a useful tool when it comes to complexity.
The idea that the principles of cellular automata are at work everywhere, at every level of the universe, has significance in any number of different scientific disciplines. Wolfram points out that the diversity of species in our world is much more easily explainable using the notion of emergent complexity, than the survival of the fittest model of mainstream evolution:
s much less theoretical heavy lifting
that the complexity
is easily produce
d from (as Wolfram puts it) simple program
s, than it is to require
that there is an evolutionary purpose
for every instance
of complex phenomena
. By Occam's razor
, it's a better model.
Another workable example is that we can imagine our own brains as vast cellular automata, with our neurons being individual cells, each obeying, deterministicly, easily understood and predictable rules. Yet, the ultimate behavior of our brains, as characterized by our minds, is complex and unpredictable. Perhaps this concept of emergent chaos can help us to demystify the link between mind and matter. We no longer need to believe that complex, unpredictable behavior must come from complex processes. And since we see neurons as being relatively simple (in that each neuron is predictable), maybe now we can see that just because neurons are simple, doesn't mean they can't support the kind of complexity that we understand directly as our own thoughts, moods, experience, and so on.
Also interesting to consider is that while cellular automata are unpredictable, they are deterministic, meaning that two identical grids with the same starting conditions will be identical to each other, every step of the way. Similarly, if our universe is ultimately deterministic (meaning, two universes with identical starting conditions would be identical to each other every step of the way), than it would still allow for the kind of unpredictable complexity we see in our day to day lives.
Wolfram's book is devoted in large part to suggesting ways in which emergent complexity can be applied to other areas of science. One of those areas is the ontological basis of the universe. Given the strength of this idea to shed light on fundamental features of our world, such as the complex forms found in nature, Wolfram is now dedicated to exploring possible ways in which the universe as we know it could unfold to its present state by way of "a few lines of code". The fruits of such labor might even provide a Grand Unified Theory.