The name is absent

In this chapter we will expose Artificial Societies (AS) and previous work that has been
made using them. But first, we will give some notions of what is a complex system, since
societies are complex systems, and we will use the terminology through this work.

2.1. Introduction to Complex Systems

“A complex object is an object which has more than one non-overlapping description”

—Jack Cohen

Indeed defining complex systems is a complex task. There are more than seventy
definitions of complexity, used in diverse areas. We can say that there are many non-
overlapping descriptions of complex systems, perhaps because it is inspired in practically all
branches of knowledge, and also because it is a very new field of study (Bar-Yam, 1997).

With this panorama, we will not attempt to define complex systems. We will only try to
describe them.

A complex system is usually constituted of many elements which interact. The
complexity of the system is proportional to the number of elements, the number of interactions
in the system, and the complexities of the elements and of their interactions. In natural complex
systems, every element is also a complex system, therefore we can only obtain a relative
complexity depending on a reference point. Since we can use various reference points, there
cannot be an absolute complexity, and each relative complexity will be different.

The global behaviour of the system arises from the interactions of the elements of the
system. In this sense, we can say that a complex system is more than the sum of its parts.

A complex system has properties not present in its parts. These properties are called
emergent. They emerge from the interactions of the components of the system.

There is not a crisp boundary between complex and simple systems. Also the complexity
of a system is strongly dependent from the context in which it is being studied. But generally
speaking, simple systems are easily predictable, have a single or few parts, and few or none
interactions. There is little or no emergence in a simple system. Examples of simple systems
might be:

•     A pendulum.

•     A bouncing ball.

•     An elevator.

We can see that the behaviour of the system might be easily predicted or described with
few rules or formulae. Also, they are not too abundant in nature. If we look around, most things
surrounding us are complex systems. Some examples might be:

•      A cell. Its function is determined by interactions of proteins. The proteins are not alive.

Life emerges from their interactions.

•     The human’s central nervous system. It is composed of millions of neurons. One neuron

is not intelligent. One brain is capable of exhibiting emergent intelligence.

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