Modular Technical Change and Genetic Algorithms
AbstractGiven knowledge is distributed across the economic population, it is appropriate to consider technical change as a process of distributed learning. This leads naturally to an evolutionary perspective. Noting the work of cognitive sciences, which uses a computational model of the mind, we are drawn to models based on genetic algorithms (GAs). Using the concept of modular technologies we are able to offer an interpretation of the GA as a model of population learning. A model involving the coevolution of implemented technologies and technological models is introduced; a highly simplified version of the model is used to assess the use of the GA approach, particularly Arifovic's augmented version. Citation Copyright 1995 by Kluwer Academic Publishers.
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Bibliographic InfoArticle provided by Society for Computational Economics in its journal Computational Economics.
Volume (Year): 8 (1995)
Issue (Month): 3 (August)
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