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In the process of modeling the real world, an important question is: should the model be as abstract as possible or as realistic as possible? Should it describes as generally as possible, or depicts as specifically as possible? One thought is that the prerequisite of grasping the overall functionality of a system is to analyze in-depth the units which comprise the system; another thought believes that the so called “individuals” have relatively strong disorderliness and randomness, thus cannot completely represent the overall behavior of the system. Constant occurrence of complexity, on the other hand, will make it difficult to discover new laws. For the first thought, the mode of construction of its system analysis is from top to bottom. The framework is basically composed of mathematical equations with relatively fewer parameters and environmental changes. It is a highly linear modeling method. For the second thought, its mode of construction of system analysis is from bottom up; the framework of the model is composed of adaptive agents, with relative more parameters and environmental uncertainty. It is a highly nonlinear modeling method. Then, what role do the research and application of cellular automata play in the clash of the two different thoughts of modeling?
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- Concluding Remarks—Looking to the Future
- Springer Singapore
- Chapter 9
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