Agent Learning Representation - Advice in Modelling Economic Learning
AbstractThis paper presents an overview on the existing learning models in the economic literature. Furthermore, it discusses which of these models should be used under what circumstances and how adequate learning models can be chosen in simulation approaches. It gives advice for getting along with the many models existing and picking the right one for the own application.
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Bibliographic InfoPaper provided by Max Planck Institute of Economics, Evolutionary Economics Group in its series Papers on Economics and Evolution with number 2004-16.
Length: 88 pages
Date of creation: Nov 2004
Date of revision:
Other versions of this item:
- Brenner, Thomas, 2006. "Agent Learning Representation: Advice on Modelling Economic Learning," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 18, pages 895-947 Elsevier.
- C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
This paper has been announced in the following NEP Reports:
- NEP-ALL-2005-01-16 (All new papers)
- NEP-CBE-2005-01-16 (Cognitive & Behavioural Economics)
- NEP-CMP-2005-01-16 (Computational Economics)
- NEP-EVO-2005-01-16 (Evolutionary Economics)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Jasmina Arifovic & John Ledyard, 2004. "Scaling Up Learning Models in Public Good Games," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 6(2), pages 203-238, 05.
- Arifovic, Jasmina, 1994. "Genetic algorithm learning and the cobweb model," Journal of Economic Dynamics and Control, Elsevier, vol. 18(1), pages 3-28, January.
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