Personal note: Researching things like this (see text that follows, read it only in the case you don't have anything better to do ) has prevented me from working with photography and graphics. The thing is that i don't have enough time to do everything. I need to have more time! BTW I'm actively searching for a time transplant, help appreciated...


Extract from my first official scientific publication:
Investigation of emergent phenomena within complex systems

Authors: O. Paunovski and Dr. G. Eleftherakis and Dr. T. Cowling
Appeard in: Proceedings of the First SEERC Doctoral Student Conference


In broad terms Complexity theory is a multidisciplinary field of research dealing with Complex Systems. There are many examples of such systems existing in nature. Cells, embryos, nervous systems, immune systems, ant colonies, etc; can all be viewed as complex systems. In the human world, cultural and social systems like political parties, scientific communities etc are also complex systems. Nevertheless these examples do not provide insight into what complex system is. An attempt at understanding and defining a complex system must start with a definition of complexity. A general view of complexity suggests that it is a property of a specific entity (presumably a system) that could be quantified. Therefore it seems logical to allocate the role of a metric to the concept of complexity. In fact there are many ways to measure complexity. For example computational complexity [2] denotes the complexity of a sequence of symbols by describing the system as finite state machine that produces this sequence. On the other hand biologists distinguish between structural and functional complexities when describing an organism, there are also many other complexity metrics used in specific domains (see [3] for more information). While each measure is useful in its own domain, there is a fundamental problem in measuring complexity. This is the inability to express complexity in a scale that will be universally accepted in all domains. In other words there are no means for measuring complexity applicable in all possible cases. This means that there is no common scale to measure and/or compare the complexity of a piece of text and biological organism. Given the nature of the problem, it seems highly unlikely that it will be solved in the near future. Consequently most of the researchers in the area of complex systems, use descriptive approaches to define complex systems. Nevertheless there is no agreement in the scientific community on a single definition. As a result there is a variety of definitions provided by different authors. For example Badii and Polity in [4] used the definition from Webster dictionary where a complex system is defined as:

“A complex object is an arrangement of parts so intricate as to be hard to understand or deal with”

On the other hand Holland’s view expressed in [5] is that:

“A complex adaptive system is complex, self-similar collection of interacting adaptive agents”

In fact the whole situation is best described by Simon in [6] where he says:

“I shall not undertake a formal definition of complex systems. Roughly by a complex system I mean one made up of a large number of parts that interact in a non-simple way”

If the definitions provided in literature are closely examined, the conclusion is that most of them revolve around two major points. First complex systems are made up of many interacting parts and second they are “not easy to be understood”. It should be noted here that the second point, referring to the concept of “not easy to be understood”, means that the system is highly complicated (or complex). Therefore one might argue that this is a subjective measure in the sense that something which is easy to understand for one person might be complicated for another. Nevertheless as complexity increases such claims become invalid. Thus it is absurd to claim that the global ecosystem of this planet is a system which is easy to understand and predict at very fine details.

References
2 Fortnow L, Homer S. A Short History of Computational Complexity. In D. van D. J Dawson, and A. Kanamori, editors, The History of Mathematical Logic. North-Holland, Amsterdam 2002/2003.
3 Adami C. What is complexity?. BioEssays 2002; 24(12):467–482.
4 Badii R, Politi A. Complexity: Hierarchical structures and scaling in physics. Cambridge: Cambridge University Press 1997.
5 Holland J H. Hidden Order: How Adaptation Builds Complexity, Addison-Wesley, 1995.
6 Herbert S. "The Architecture of Complexity" in Proceedings of the American Philosophical Society 1962, 106:467-482.