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--- abstract: 'This article aims to test the relevance of learning through Genetic Algorithms (GA) and Learning Classifier Systems (LCS), in opposition with fixed R&D rules, in a simplified version of the evolutionary industry model of Nelson and Winter. These three R&D strategies are compared from the points of view of industry performance (welfare): the results of simulations clearly show that learning is a source of technological and social efficiency.' altloc: - http://147.210.86.202/ifrede/e3i/publications/WP/article.php3?SELECTWP=2001-1 chapter: ~ commentary: ~ commref: ~ confdates: ~ conference: ~ confloc: ~ contact_email: ~ creators_id: - yildi creators_name: - family: Yildizoglu given: Murat honourific: '' lineage: '' date: 2001 date_type: published datestamp: 2004-10-08 department: ~ dir: disk0/00/00/38/64 edit_lock_since: ~ edit_lock_until: ~ edit_lock_user: ~ editors_id: [] editors_name: [] eprint_status: archive eprintid: 3864 fileinfo: /style/images/fileicons/application_pdf.png;/3864/1/2001%2D1.pdf full_text_status: public importid: ~ institution: ~ isbn: ~ ispublished: ~ issn: ~ item_issues_comment: [] item_issues_count: 0 item_issues_description: [] item_issues_id: [] item_issues_reported_by: [] item_issues_resolved_by: [] item_issues_status: [] item_issues_timestamp: [] item_issues_type: [] keywords: ' Learning, Learning Classifier Systems, Bounded Rationality, Technical Progress, Innovation' lastmod: 2011-03-11 08:55:42 latitude: ~ longitude: ~ metadata_visibility: show note: 'JEL Classification: O3, L1, D83' number: ~ pagerange: ~ pubdom: FALSE publication: ~ publisher: ~ refereed: FALSE referencetext: |- Butz, M. V. [2000], XCSJava 1.0: An Implementation of the XCS classifier system in Java , Technical Report 2000027, Illinois Genetic Algorithms Laboratory. Butz, M. V. & Wilson, S.W. [2000], An Algorithmic Description of XCS, Technical Report 2000017, Illinois Genetic Algorithms Laboratory. Goldberg, D. E. [1991], Genetic Algorithms, Addison-Wesley, Reading: MA. Jonard, N. & Yildizoglu, M. [1998], ‘Technological diversity in an evolutionary industry model with localized learning and network externalities’, Structural Change and Economic Dynamics 9(1), 35–55. Knight, F. H. [1921], Risk, Uncertainty and Profits, number Reprint, Chicago University Press, Chicago. Kwasnicki,W.& Kwasnicka, H. [1992], ‘Market, innovation, competition. an evolutionary model of industrial dynamics’, Journal of Economic Behavior and Organization 19, 343–368. Lanzi, P. L., Stoltzmann, W. & Wilson, S. W. [2000], Learning Classifier Systems. From Foundations to Applications, Vol. 1813 of LNAI, Springer, Berlin. Nelson, R. R. & Winter, S. [1982], An Evolutionary Theory of Economic Change, The Belknap Press of Harvard University, London. Oltra, V. & Yildizoglu, M. [1999], ‘Expectations and adaptive behaviour: the missing trade-off in models of innovation’, WP BETA No. 9905, Universite Louis Pasteur, Strasbourg . Silverberg, G., Dosi, G. & Orsenigo, L. [1988], ‘Innovation, diversity and diffusion: a self-organization model’, Economic Journal 98, 1032–1054. Silverberg, J. & Verspagen, B. [1996], From the artificial to the endogenous, in M. Helmstadter, Ernst; Perlman, ed., ‘Behavioral norms, technological progress, and economic dynamics: Studies in Schumpeterian economics’, University of Michigan Press, Ann Arbor. Simon, H. A. [1958], The role of expectations in adaptive or behavoristic model, in M. Bowman, ed., ‘Expectations, Uncertainty and Business Behavior’, Social Science Council, New York, pp. 49–58. Simon, H. A. [1976], From substantial to procedural rationality, in Latsis, S. J. (ed), Method and Appraisal in Economics, Cambridge University Press, Cambridge, pp. 129–148. Watson, C. J., Billingsley, D. J., Croft, D. J. & Huntsberger, D. V. [1993], Statistics for Management and Economics, fifth edition, Allyn and Bacon, Boston. Wilson, S. W. [1995], ‘Classifier Fitness Based on Accuracy’, Evolutionary Computation 3(2), 149–175. http://prediction-dynamics.com/. Yildizoglu, M. [2001], ‘Competing r&d strategies in an evolutionary industry model’, forthcoming in Computational Economics. Available at http://yildizoglu.montesquieu.u-bordeaux.fr/ . relation_type: [] relation_uri: [] reportno: ~ rev_number: 12 series: ~ source: ~ status_changed: 2007-09-12 16:53:55 subjects: - comp-sci-mach-learn - socsim succeeds: ~ suggestions: ~ sword_depositor: ~ sword_slug: ~ thesistype: ~ title: 'Modeling Adaptive Learning: R&D Strategies in the Model of Nelson & Winter (1982)' type: preprint userid: 5133 volume: ~