Abstract
The strength of physical science lies in its ability to explain phenomena as well as make prediction based on observable, repeatable phenomena according to known laws. Science is particularly weak in examining unique, non-repeatable events. We try to piece together the knowledge of evolution with the help of biology, informatics and physics to describe a complex evolutionary structure with unpredictable behavior. Evolution is a procedure where matter, energy, and information come together. Our research can be regarded as a natural extension of Darwin’s evolutionary view of the last century. We would like to find plausible uniformitarian mechanisms for evolution of complex systems. Workers with specialized training in overlapping disciplines can bring new insights to an area of study, enabling them to make original contributions. This chapter describes evolution of complexity as a basic principle of evolutionary computation.
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Ošmera, P. (2013). Basic Principle of Evolutionary Computation. In: Zelinka, I., Snášel, V., Abraham, A. (eds) Handbook of Optimization. Intelligent Systems Reference Library, vol 38. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30504-7_42
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DOI: https://doi.org/10.1007/978-3-642-30504-7_42
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