Complexity in science is a field of study devoted to the process of self-organization. The basic concept of complexity is that all things tend to organize themselves into fractal patterns, e.g., artificial life simulations, traffic networks, the interplay between supply and demand in an economy, bee hives, ant colonies, immune systems, relationships among living organisms in an ecosystem, and human cultures. The more complex a task the harder it is to think about and the steeper the learning curve.
Complex systems are characterized by unpredictable behaviour, existing in a state somewhere between order and chaos. Things that are complex in nature exhibit characteristics like cycles of growth, mass extinction, regeneration and evolution.
It has been noted that natural forces tend to bring complex systems to a halt, suddenly and unexpedictedly. This is related to chaos theory and the general rule that small changes to a system, may bring a dramatic change in the future. Complexity looks for the mathematical equations that describe the middle ground between equilibrium and chaos (nonlinear dynamics).
Many cultures tend to the use of rules to counter problems related to human interaction and complexity. There are many examples of complex systems with unpredictable behaviour. Take a stampede at a religious festival, or a design flaw in a rocket design. Another example, the human world as a whole is a very complicated affair, which has grown into the “Club of Rome created the concept of “World Problematique” It is summarized as follows:
- “The complexity of the world problematique lies in the high level of mutual interdependence of all these problems on the one hand, and in the long time it often takes until the impact of the action and reaction in this complex system becomes visible.”
Complexity and Computers
In computer science, complexity measures how difficult a problem is to solve. When something is complicated it is harder to administer and manage. The problem is that while we may know of an algorithm that solves a problem, it will take a computer too long to solve it. The issue of security vulnerabilities is complex due the the nature of the network communications and the human element. Likewise, Copyright, patents, privacy and free speech are problematic. Modern, mass communications with information technology amplify the social aspects by all sorts of varying networks, applications, languages, chat rooms, etc.
As system become more complex they are prone to increased security risk. Microsofts attempts to supress the darknet with DRM technology or tie users to a proprietary platform are likely to decline and fail because the complexity of the required code and its incompatibility with users security needs, will make their product too undesirable.
This chaotic conundrum can lead to political consequences when issues such as accountability arise. Democractic capitalism appears to be the dominant political response to social self-organisation, but other forms such as open source are being nurtured with the internet.
- Emergence – Journal Archive
- Complexity Digest
- Links on Complexity, Self-organization and Artificial Life at Principia Cybernetica Web
- The Complexity & Artificial Life Research Concept – Dedicated to modern systems thinking in all its various forms.
- Complexity, Self Adaptive Complex Systems, and Chaos Theory
Many of the following topics are inherently complex;
- Adaptive programs
- Artificial Intelligence
- Content management system
- Cryptography – relates computational power with the difficulty to crack a cipher. This becomes a very complex topic. Hardened Criminal’s HardEncrypt describes one of many angles.
- Data haven
- Fuzzy Logic
- Gift Economy Data
- Information Retrieval
- Natural Language Processing
- Persistent Online Worlds
- Quantum Computing
- Realistic computer grahics
- Semantic Web
- Syntax Highlighting
TakeDown.NET -> “Complexity”