The study of systems starts with the recognition that systems are emergent. This means that systems behave in ways that go beyond the behavior of their parts.
To understand an emergent system, you cannot merely study the behavior of its parts and stop there. New behaviors come from interactions between these parts, and a new set of intellectual tools are required to reason about these behaviors. This includes several principles cataloged in this index, including feedback, critical phenomena, and evolution.
Before we get into these powerful intellectual tools, let’s take our first direct glimpse of emergence in action.
In thinking about systems, it is helpful to start with simple models which are easy to think about and run on computers. So let’s start with a super-simple model – freezing particles.
The parts of this system are the particles. Particles are simple – all they do is move randomly and stick together sometimes. We would expect the behavior of a system made of many of these particles to be just as simple. One good guess: blobs of particles will grow around any frozen “seeds”.
So let’s find out! Here is a system with one hundred times as many particles as the little boxes above:
When you’re ready, .
The result doesn’t match our guess at all. Instead of forming a blob, freezing particles grow outward from the seed, like a tree’s roots or electric sparks.
Together, the particles make a pattern which was not encoded in their rules. We didn’t tell the particles to make a branching pattern. The pattern emerged.
To see how the pattern continues, at a higher level of scale, here is a system with nine times as many particles as last time:
When you’re ready, .