| Auerswald, P., S. Kau#man, J. Lobo, and K. Shell (2000) "The Production Recipes Approach to Modeling Technological Innovation: An Application to Learning by Doing," Journal of Economic Dynamics and Control, 24, 389-450. |
.... the NK model, which has been originally developed as a model of biological evolution of complex organisms (Kauffman 1988, 1993, 1995) Recently, this model has been used in simulation exercises concerning the optimisation of complex technological systems by competing agents (Kauffman et al. 1998; Auerswald et al. 2000). As for neoclassical models, these applications concerned models of process innovation, too. Here, we generalise the model to describe product innovation using Altenberg s (1997) extension of the NK model. 2.1 Kauffman s NK model 2.1.1 Complexity Complex systems are systems containing elements ....
.... developed as a model of biological evolution, but its formal structure allows for applications in the domain of technological evolution through human search activity (e.g. Kauffman 1988, 1993, 1995; Kauffman and Macready 1995; Kauffman et al. 1998; Frenken et al. 1998, 1999a; Marengo 1998; Auerswald et al. 2000; Valente 2000) 4 as well as applications in other domains. 5 Kauffman describes a system by a string of N elements (n=1, N) For each element n, there exist a number of dummy values called alleles that refer to the possible variants of this element. The different alleles of an element ....
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Auerswald P., Kauffman S., Lobo J., Shell K. (2000) `The production recipes approach to modeling technological innovation: an application to learning-by-doing', Journal of Economic Dynamics And Control 24, pp. 389-450.
....eventually arrive at its globally optimal configuration, since each agent will ultimately find its best state when there is no correlation between groups (J = 0) The economy s expected average payoff at this optimum is 0. 67, the expected value of the larger of two independent draws from a uniform [0,1] distribution 3 . Consider now the case when L = 2 with J = 0 and S = 2: The outcomes for two agents within the same group are linked. There are four possible states for each group [ g 2 f00; 01; 10; 11g] The best result is to pick the highest of the four payoffs; however, since the payoffs ....
.... Searches Searching for optimal configurations is an extremely difficult combinatorial problem for which analytic solutions are not known, except in several limiting cases (e.g. L = 1; J = 0) 3 The expected value of yn , the largest of n random variables drawn independently from a uniform [0,1] distribution, equals n= n 1) For a treatment of order statistics see Mood, Graybill and Boes (1974) 0 0 0 0 1 1 1 1 0.4 0.6 0.5 0.1 0.3 0.2 0.3 0.9 0.6 0.9 0.7 0.8 Figure 3: Possible payoffs for a group of size L = 2 with S = 2 and J = 0. The decimal numbers inside each box denote the ....
Auerswald, P., S. Kauffman, J. Lobo and K. Shell (1998) "The Production Recipes Approach to Modeling Technological Innovation: An Application to Learning by Doing. " Center for Analytic Economics Working Paper 98-10, Ithaca: Cornell University. (Forthcoming in Journal of Economic Dynamics and Control.)
No context found.
Auerswald, P., S. Kau#man, J. Lobo, and K. Shell (2000) "The Production Recipes Approach to Modeling Technological Innovation: An Application to Learning by Doing," Journal of Economic Dynamics and Control, 24, 389-450.
No context found.
Auerswald, P., S. Kauffman, J. Lobo, and K. Shell (1998), "The Production Recipes Ap- proach to Modeling Technological Innovation: An Application to Learning By Doing," Cornell University, CAE Working Paper 98-10.
No context found.
Auerswald, P., S. Kauffman, J. Lobo, and K. Shell (1998), "The Production Recipes Ap- proach to Modeling Technological Innovation: An Application to Learning By Doing," Cornell University, CAE Working Paper 98-10.
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