caa a22 4500 445854421 CHVBK 20180317145424.0 cr unu---uuuuu 170323e20111201xx s 000 0 eng 10.1007/s00191-010-0193-1 doi (NATIONALLICENCE)springer-10.1007/s00191-010-0193-1 Geisendorf Sylvie Section Environmental and Behavioural Economics, University of Kassel, Nora-Platiel-Str. 4, 34109, Kassel, Germany aut Internal selection and market selection in economic Genetic Algorithms [Elektronische Daten] [Sylvie Geisendorf] Genetic algorithms have been established as an alternative to neoclassical optimization for the illustration of economic agents' behavior. Critics however, doubt they depict the particularities of social evolution, because they fail to describe intentional behavior. The current paper argues that advocates as well as critics of the procedure have overlooked the crucial necessity to distinguish between internal and external selection in the economy and to include both in economic Genetic Algorithms. The paper claims that such a differentiation will allow the model to depict intentional decisions as well as market selection and help to understand the effects of bounded rationality. It illustrates this point with a brief example modeled after the new-versus-new competition between lean-burn engines and catalysts in the 70th. Springer-Verlag, 2010 Genetic Algorithms nationallicence Internal selection nationallicence Intentionality nationallicence External selection nationallicence Bounded rationality nationallicence Economic evolution nationallicence Journal of Evolutionary Economics Springer-Verlag 21/5(2011-12-01), 817-841 0936-9937 21:5<817 2011 21 191 https://doi.org/10.1007/s00191-010-0193-1 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s00191-010-0193-1 text/html Onlinezugriff via DOI NATIONALLICENCE 100 1- Geisendorf Sylvie Section Environmental and Behavioural Economics, University of Kassel, Nora-Platiel-Str. 4, 34109, Kassel, Germany aut NATIONALLICENCE 773 0- Journal of Evolutionary Economics Springer-Verlag 21/5(2011-12-01), 817-841 0936-9937 21:5<817 2011 21 191 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer