Complexity and complex systems
Science generally uses a system called reductionism to investigate our world. This means breaking down anything being examined into the parts that make it up. Reductionism proposes that if we understand the parts, we will understand how the whole system works. But often using this approach we miss the bigger picture. Sometimes the way the parts interact is critical to how the whole system works. This is what complexity studies.
Most of the open questions in psychology, computer science, biology, medicine and physics have something to do with emergence, complexity and complex systems:
- Is evolution truly random?
- How can we understand complex diseases like Cancer and Alzheimer?
- How does the mind work? Why do we sleep?
- Is there a simple fundamental physical theory at the Planck scale?
- How can we create true artificial intelligence?
Complexity is relevant to an enormous range of areas of study including traffic flows, earthquakes, the stock market, Jupiter’s red spot, group dynamics, airline networks, the spread of viruses, the internet, urban planning and much more. Prof. Stephen Hawking has stated, “The next century will be the century of complexity”. Several concepts used in Complexity have come into mainstream use, such as tipping points, the butterfly effect and six degrees of separation.
A complex system is one in which numerous independent elements continuously interact and spontaneously organize and reorganize themselves into more and more elaborate structures over time. Complexity is characterized by:
(1) A large number of similar but independent elements or agents;
(2) Persistent movement and responses by these elements to other agents;
(3) Addictiveness so that the system adjusts to new situations to ensure survival;
(4) Spontaneously and non-predictable self-organization
(5) Local rules that apply to each agent; and
(6) Progression in complexity so that over time the system become larger and more sophisticated.
Life is caught in the tension between order and chaos. If there is too much order, everything becomes the same and there is no room for creativity or anything new. Everything must fit the one pattern. If there is too much chaos nothing can last long enough to create anything useful; everything is just a jumble that destroys everything before it can get started. Between order and chaos is found the Edge of Chaos, the point where there is enough chaos for novelty and creativity, but also enough order for consistency and patterns to endure. This point is a magic point, where new and unimagined properties can emerge.
The important common questions about complex adaptive systems (CAS) are the questions about the emergence of complexity, the role of self-organization, cooperation and specialization.
Emergence
Emergence out of nothing is an illusion. Global structures and phenomena can suddenly emerge from simple local interactions, because other structures or species are subject to extinction, dissipation or destruction.
Self-organization
Systems without organizator organize themselves to higher and higher levels of complexity, because they are open and not isolated, which allows them to extract information, energy and complexity from their environment.
Cooperation
Selfish agents cooperate with each other to form larger groups, teams and clusters of agents, because they use and exploit others to help themselves. Agents usually still act on their own behalf if they are supporting others.
Specialization
Agents are able to produce an aggregate or composite entity that is more flexible and adaptive than its components, because specialization and division of labor increases flexibility and adaptability.
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