Modular technical change and genetic algorithms
| Autor: | Chris Birchenhall |
|---|---|
| Rok vydání: | 1995 |
| Předmět: |
education.field_of_study
Interpretation (logic) Computer science Process (engineering) business.industry Economics Econometrics and Finance (miscellaneous) Perspective (graphical) Population Modular design Technical change Computer Science Applications Genetic algorithm Artificial intelligence education business Coevolution |
| Zdroj: | Computational Economics. 8:233-253 |
| ISSN: | 1572-9974 0927-7099 |
| DOI: | 10.1007/bf01298461 |
| Popis: | Given 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 in introduced; a highly simplified version of the model is used to assess the use of the GA approach, particularly Arifovic's augmented version. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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