Abstract
The relationship between biology and economics has been long: it is said that 150 years ago both Wallace and Darwin were influenced by Malthus’ writings on the rising pressures on people in a world in which human population numbers grew geometrically while food production only grew arithmetically. In the early 1950s there was an awakening that the processes of market competition in a sense mimicked those of natural selection. This thread has followed through to the present, in an “evolutionary” approach to industrial organization. Recently, however, computer scientists and economists have begun to apply principles borrowed from biology to a variety of complex problems in optimization and in modelling the adaptation and change that occurs in real-world economic problems.
The first author wishes to acknowledge the support of the Australian Research Council.
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Marks, R.E., Schnabl, H. (1999). Genetic Algorithms and Neural Networks: A Comparison Based on the Repeated Prisoners Dilemma. In: Brenner, T. (eds) Computational Techniques for Modelling Learning in Economics. Advances in Computational Economics, vol 11. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-5029-7_8
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