Download This PaperModeling Adaptive Learning: R&D Strategies in the Model of Nelson & Winter (1982)
E3i Working Paper No. 2001-1
15 Pages Posted: 5 Apr 2004
Date Written: 2001
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.
Keywords: Learning, Learning Classifier Systems, Bounded Rationality, Technical Progress, Innovation
JEL Classification: O3, L1, D83
Suggested Citation: Suggested Citation
Yildizoglu, Murat, Modeling Adaptive Learning: R&D Strategies in the Model of Nelson & Winter (1982) (2001). E3i Working Paper No. 2001-1, Available at SSRN: https://ssrn.com/abstract=516582 or http://dx.doi.org/10.2139/ssrn.516582
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