One way to examine what may be happening in self-organizing complex systems is through the use of computer simulations. Two free software programs, StarLogo (“Starlogo”, 2004) and NetLogo (Wilensky, 1999, 2004), offer users opportunities to witness self-organization in action by modeling the dynamics of complex systems. The Logo language, which is the foundation of these modeling systems, was developed by Seymour Papert at MIT in order to teach children the basics of computer programming. As such, it is user-friendly and easy to learn. The novice can explore models that are included in the model libraries, manipulating the variables through sliders and simple commands. Those with greater interest or more experience can create models of their own. Because of their accessibility and ease of use, these software programs can be found in labs and classrooms all over the world.
The three main components of the modeling environment are turtles, patches, and the observer. The individual agents in the system are called turtles, although they can represent any kind of agent from a molecule to a person. The environment in which the turtles operate is divided into patches. Patch size and movement by turtles within and between patches is determined by the program designer. Patches are not necessarily passive but may be, and typically are, active components of the system. Commands may apply either to turtles or to patches. The third component, the observer, can issue commands that affect both patches and turtles. The observer also conducts maintenance and documentation of the turtle world.
Variables within a model may be set up as sliders, and in many models the sliders can be manipulated while the model is running. This feature allows the user to alter variables and search for excellent solutions within the constraints identified by the model designer. For example, a simple model of an ecosystem might include agents identified as predators, other agents called prey and patches with food for the prey in varying amounts. The interactions between the two different kinds of agents, as well as between the agents and the patches, can be defined by simple commands that identify when predators eat prey, when prey eat food, under what conditions new agents are “born” and “die,” and so on. If such a model is designed with sliders to control the numer of predators and prey, as well as the proportion of food available, the user can experiment to try to determine how a change in one part of the system affects the system as a whole and how a system might adapt in order to survive or thrive.
The beauty of these modeling tools with regard to building the scientific mind is that they provide the user with a dynamic visual and interactive medium through which to explore the concepts of complex systems. They are simple enough to be used by students in middle or high school, while at the same time they have the potential sophistication required of graduate level research. As such, the use of these free modeling tools opens up the world of complex systems to a broad audience, including those without advanced understanding of science and mathematics. The medium itself can describe and explain, through color, pattern and motion, concepts that previously might have been incomprehensible.