Complex system theory in animals and machines is well developed and a basic synopsis is provided. The evolutionary process of natural selection has been described starting with the formation of complex structures (Costa, 2002). The studies of Biology, and more recently Cognitive Science have contributed to the ideas of complex systems, this is explored using the concept of homeostasis (Campbell, 1993). These ideas have been applied in the field of Engineering to develop machines for controlling states of objects or events: a simple temperature control system is used as a model. Evolutionary parallels are cited between the biological and mechanical types of control systems.
The purpose of a complex system is to modify its internal state such that it replicates the "ideal" state for that system. This is achieved by comparing actual and desired states (Downing, 2002), taking corrective action by utilising the processes it can control to manipulate its state as close to the ideal state as possible. An example in nature of a complex system is homeostasis. This control system can be linked through evolution to the steady state reached by macromolecules millions of years ago. These theories of "control systems" such as homeostasis have been applied mechanically to produce various complex systems such as room temperature control by a heating device. .
The most important role of a complex system is, having an ideal state/output, to measure the state/output and have the ability to regulate itself to maintain its ideal state/output. To achieve this, complex systems must have a performance criteria (Downing, 2002), a measurement input of this criteria and then mechanisms to effect change in performance. .
Campbell (1993) describes biological systems as utilising nerve cells called receptors as input devices, and nerve cells called effectors as output devices. Complex cognitive systems within the brain act as the control centre for evaluating ideal performance criteria.