Backdoor Man

1.) Introduction

In this essay I am going to look into the world of complexity the the phenomena of emergence. I am first going to define emergence and give a broad example of the use of emergence in a practical example. Through the work of Mill and Huxley and other contemporary scholars on the subject of complexity and emergence, I am going to give a theoretical outline of how this fits into systems theory.

2.) Definition

What is emergence?

Jackson(2005) defines emergence as:

“The whole containing properties not reducible to the parts but generated by interactions parts, between the parts.”

Emergence can’t be defined as a stand-alone concept. It is a direct component of complexity theory. To understand the meaning of emergence we first need to look at the theory itself as part of systems theory, which I am going to discuss now.

Systems form part of everyday life, they are part of out abstract thoughts and problem to things we observe in nature. Systems theory also covers systems within organizations and tries to give meaning and solutions to the problems we face within them. So let’s briefly look at what is a system. A broad definition from M. Jackson follows as ‘a system is a complex whole the functioning of which depends on its parts and the interactions between those parts.’ So systems can be organic, or non organic, systems can be, physical, biological, designed, abstract, social or even simple human activity.

• Physical systems, such as river systems;

• biological systems, such as living organisms;

• designed, such as steam engine;

• abstract, such as philosophical systems;

• social, such as families;

• human activity, such as systems to ensure quality of products.

In Jackson’s definition he makes it clear that these systems can be complex, not to be confused with complicated. This means that systems are very hard to be defined or understood if possible at all, it is therefore complex. Complexity on the other hand also refers to system of many parts, but all those parts function’s and behaviour are known and behave according to a calculated prediction.

A good boerewors is complex(not mass market boerewors, but those home made ones that is the pride of every farmer’s wife), it’s almost impossible to predict or understand how the diverse mix of herbs, selection of meat and fat will react over a couple of hot coals. The relationship of all these elements is so hard to understand that it’s impossible to make the exact same boerewors time after time. An auto mobile on the other hand is a form of a complicated system. Even the highest class super cars can be put together the exact same way, their performance and interactions between the sum of it’s parts can be predicted beforehand, through reduction every part serves a function that can be understood.

Now the link should be able to seen in the relation between the term emergence and complex systems. Emergence is that phenomena that makes that good home made boerewors taste the way it does. Emergence is that relationship of interactions between the mixed herbs and spices with the meat and fat over a fire with unique behaviour to deliver that end resulting taste.

3. ) Emergent Behaviour

“It is the whole that produced the whole, rather than any part a part.” (Mill, p. 347)

Even behaviour of the simplest of entities within an environment can deliver complex behaviour in a collective form. A termite nest for instance is a the emergent result of simple behaviour of termites. The behaviour of these small creatures can be analysed and predicted, but the end result of the behaviour of hundreds of termites portraying the same behaviour patterns is hardly predictable as they deliver complex results.

The reason why this end result of collective behaviour is hard to predict, is because of the large number of interactions between the different behaviour agents. However a large amount of interactions does not directly translate to complex systems. This is because some interactions can cancel each other out or become irrelevant within the system. A group of life hackers at MIT have an simple life rules simulations based on Conway’s Game of Life where this theory can be tested.

Here is one example of a simple set of rules simulating behaviour of an agent.

If a square is on, it turns off. If a square is off, it turns on if exactly two of its eight neighbouring squares are on.

The above object is called a glider. The simple rules above gives this glider a steady motion towards the right of the block through every iteration of the rule set. It’s behaviour can be predicted before it goes through a process of simulation.

The following four blocks behaviour is also constrained by the same set of rules as the above glider.

After each iteration of the rules the system becomes a lot more complex. The above images only went through a handful of iterations, when it goes through a couple hundred it becomes very complex and increasingly difficult to predict or calculate what will happen with the next iteration. These are basic objects and their behaviour is not influenced by external sources. If we add a random block in the last image, the pattern will become almost impossible to predict and it becomes chaotic where it once gave isometric patterns.

We still have to remember however that large amounts of interactions are not a guarantee that emergent behaviour will emerge. It is how the interactions are organised within the system.

(Resnick M,. Silverman B. (1996), “Exploring Emergence”)

(Corning, Peter A. (2002), “The Re-Emergence of “Emergence”: A Venerable Concept in Search of a Theory“)

4.) Emergent structures life.

Emergence is a occurrence within a system, for this reason emergent structures can be found in various forms just like they systems they are part of. Emergent structures can be found in living or non living systems, it could be found in physical or abstract systems.

Like the example that I have already given about the termite nest, emergence is also found throughout the animal kingdom. Flocking of birds and fish is a example of these emergent structures in living biological systems. These structures are good examples to illustrate Conway’s Game of Life where a simple number of rules give meaning to the way some creatures will behave and why patterns emerge from this behaviour. The most basic form of life, proteins are also the emergent result of atoms forming folded polypeptide chains that gives protein their structure.

In non living physical systems behaviour of microscopic agents such as atoms interact in such a way that a phenomena emerges on a more macro observable scale. A good example of such a system is the colour of light. Only when atoms within light particles are are arranged in a specific way do they absorb or emit a wavelength of light that gives us colour of a physical object.

Emergence can also be found in politics, and economics. Patterns or structures of emergence also arise when we commute. Markets are a prime example of complex financial systems. There is almost no underlying pattern as markets fluctuate and in some cases like the dot com bubble, crash. Although good investors can do their homework there is no guarantee that they will succeed with their investment in every situations as markets can be highly volatile to change.

(Crutchfield, James P. (1994), The Calculi of Emergence: Computation, Dynamics, and Induction, “Special issue on the Proceedings of the Oji International Seminar: Complex Systems — from Complex Dynamics to Artificial Reality”, California: Berkeley)