A way of modelling a Complex Adaptive System. A system with high adaptive capacity exerts complex adaptive behavior properties of complex numbers pdf a changing environment. The study of CAS focuses on complex, emergent and macroscopic properties of the system.
CAS “are systems that have a large numbers of components, often called agents, that interact and adapt or learn. CAS can be hierarchical, but more often exhibit aspects of “self-organization. A CAS is a complex, self-similar collectivity of interacting, adaptive agents. They can be found on all levels: cells specialize, adapt and reproduce themselves just like larger organisms do. Communication and cooperation take place on all levels, from the agent to the system level.
Such interactions are rich, i. Any interaction can feed back onto itself directly or after a number of intervening stages. Such feedback can vary in quality. Complex systems have a history. Agent-based models are developed by means of various methods and tools primarily by means of first identifying the different agents inside the model. Another method of developing models for CAS involves developing complex network models by means of using interaction data of various CAS components.
Passive versus active trends in the evolution of complexity. CAS at the beginning of the processes are colored red. Changes in the number of systems are shown by the height of the bars, with each set of graphs moving up in a time series. Living organisms are complex adaptive systems. This observation has led to the common misconception of evolution being progressive and leading towards what are viewed as “higher organisms”. If this were generally true, evolution would possess an active trend towards complexity.