This file is part of IDEAS, which uses RePEc data


[ Papers | Articles | Software | Books | Chapters | Authors | Institutions | JEL Classification | NEP reports | Search | New papers by email | Author registration | Rankings | Volunteers | FAQ | Blog | Help! ]

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

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
Murat Yildizoglu

Additional information is available for the following registered author(s):

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.

Download Info
To download:

If you experience problems downloading a file, check if you have the proper application to view it first. Information about this may be contained in the File-Format links below. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://beagle.u-bordeaux4.fr/ifrede/e3i/publications/2001/2001-1.pdf
Our checks indicate that this address may not be valid because: 404 Not Found. If this is indeed the case, please notify (Vincent Frigant)
File Format: application/pdf
File Function:
Download Restriction: no

Publisher Info
Paper provided by Equipe Industries Innovation Institutions, Université Bordeaux IV, France in its series Working Papers with number 2001-1.

Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Length:
Date of creation: 2001
Date of revision:
Handle: RePEc:iii:wpeiii:2001-1

Contact details of provider:
Postal: Avenue L�on Duguit, 33608 Pessac Cedex
Phone: 05.56.84.54.53
Fax: 05.56.84.86.47
Email:
Web page: http://www.gretha.fr/
More information through EDIRC

For technical questions regarding this item, or to correct its listing, contact: (Vincent Frigant).

Related research
Keywords: Learning; Learning Classifier Systems; Bounded Rationality; Technical Progress; Innovation;

Find related papers by JEL classification:
O3 - Economic Development, Technological Change, and Growth - - Technological Change
L1 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance
D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search, Learning, and Information

This paper has been announced in the following NEP Reports:

Statistics
Access and download statistics

Did you know? RePEc data is maintained by each archive holder on its own website. Nothing is held centrally.

This page was last updated on 2009-11-27.

This information is provided to you by IDEAS at the Department of Economics, College of Liberal Arts and Sciences, University of Connecticut using RePEc data on a server sponsored by the Society for Economic Dynamics.