Modeling Adaptive Learning: R&D Strategies in the Model of Nelson & Winter (1982)

Yildizoglu, Murat (2001) Modeling Adaptive Learning: R&D Strategies in the Model of Nelson & Winter (1982). [Preprint]

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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.

Item Type:Preprint
Additional Information:JEL Classification: O3, L1, D83
Keywords: Learning, Learning Classifier Systems, Bounded Rationality, Technical Progress, Innovation
Subjects:Computer Science > Machine Learning
Psychology > Social Psychology > Social simulation
ID Code:3864
Deposited By: Yildizoglu, Prof. Murat
Deposited On:08 Oct 2004
Last Modified:11 Mar 2011 08:55

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