One important aspect of Complexity Science is the idea of “emergence” or “self-organization,” where simple rules or circumstances lead to events that are not scripted. In other words, where things seem to take on “a life of their own.” The iOS Apps Life Game Touch and LifeGameHD speeder do a good job of demonstrating the cellular automation “game,” Conway’s Game of Life.
Complexity lovers and learners alike will fall in love with the new Complexity Science magazine on Flipboard. With selections from Jake David and other contributors, this magazine aims to “observe complex and emergent phenomenon in science, society, and art.” In other words, it brings together articles that might not seem related to Complexity Science together for the complexity reader.
Advantages and Disadvantages of Simulation Applications of simulation are helpful to scientists and researchers, but they come with a set of advantages and disadvantages.
Complexity Science is a relatively new approach to understanding the systems in our lives. Complex systems and complexity science deal with systems that cannot be easily/perfectly predicted (such as the movement of the planets or the weather) or simplified down to a probability (such as flipping a coin or describing the behavior of gas molecules in a room).
In the realm of Complexity Science, many people talk about how things are “Complex” but they aren’t “Complicated”. The problem is that the two terms can be hard to distinguish.
This video from TedTalks is a good overview of the concept of complexity. This is a video from www.ted.com.
If you take a purely determinate function and iterate it over time difficult-to-predict behavior can emerge. If you only use the same function, then the outcome is easily determined and therefore not complex. But if you use more than one determinate function or a set of rules with simple determinate functions then difficult-to-predict behavior may emerge.
In order to begin to understand complexity, we need to discover what complexity is not. Complexity is the region between the polar opposites, Determinate and Probabilistic. Something determinate can be predicted with certainty. Something probabilistic can be predicted within some statistical bounds (like the flipping of a coin). While complexity includes elements of both of these, it is neither determinate nor probabilistic.