Computable Learning, Neural Networks and Institutions
We propose a tractable simplification of Gold's (1965, 1967) inductive inference model based on neural networks. In this way, we can introduce explicitly institutions in a learning model. In particular, the hidden layer of neural network is shown to perform certain functions-data preprocessing and uncertainty and complexity reduction-that are typically attributed to institutions. In an evolutionary context based on selection and successive generations, we study under what circumstances individuals employing particular institutions-that improve their learning capabilities-are successful. Simultaneously, we are interested in how this process determines the adoption of different institutions in the population. From this perspective, this paper can be considered a contribution to the literature dealing with the emergence of a dominant design. We record lock-in phenomena as well as ``adoption externalities. However, our main goal is that of showing that in the context of a major change in the environment, the more rigid and strictly specialized an institution is, the longer and more complex the learning process will be of any economic actor subject to the by-now obsolete institution. The metaphor we suggest is for the firm intended as organization and productive process. A major change in the environment is, in this case, the introduction of an innovation or of compulsory standards. By describing an economic actor in structural terms-via neural networks-, we automatically impose bounded rationality. This is so because each agent will behave according to well defined procedures, but also because of the obvious cognitive and computational limitations.
|Date of creation:|
|Contact details of provider:|| Postal: Department of Econometrics, University of Geneva, 102 Bd Carl-Vogt, 1211 Geneva 4, Switzerland|
Web page: http://www.unige.ch/ce/ce96/welcome.html
More information through EDIRC
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.:
- Spear, Stephen E, 1989. "Learning Rational Expectations under Computability Constraints," Econometrica, Econometric Society, vol. 57(4), pages 889-910, July.
- Simon, Herbert A, 1978. "Rationality as Process and as Product of Thought," American Economic Review, American Economic Association, vol. 68(2), pages 1-16, May.
- J.P. Fitoussi & K. Velupillai, 1990. "Macroeconomic Perspectives," UCLA Economics Working Papers 609, UCLA Department of Economics.
- Francesco Luna, "undated". "The Emergence of a Firm as a Complex-Problem Solver," Computing in Economics and Finance 1997 166, Society for Computational Economics.
- Velupillai, K., 2000. "Computable Economics: The Arne Ryde Memorial Lectures," OUP Catalogue, Oxford University Press, number 9780198295273, April.
- Rustem, Berc & Velupillai, Kumaraswamy, 1990. "Rationality, computability, and complexity," Journal of Economic Dynamics and Control, Elsevier, vol. 14(2), pages 419-432, May.
When requesting a correction, please mention this item's handle: RePEc:sce:scecf6:_037. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F. Baum)
If references are entirely missing, you can add them using this form.