Connecting adaptive behaviour and expectations in models of innovation: The Potential Role of Artificial Neural Networks
AbstractIn this methodological work I explore the possibility of explicitly modelling expec-tations conditioning the R&D decisions of firms. In order to isolate this problem from the controversies of cognitive science, I propose a black box strategy through the concept of internal model . The last part of the article uses artificial neural networks to model the expectations of firms in a model of industry dynamics based on Nelson & Winter (1982).
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Bibliographic InfoPaper provided by Society for Computational Economics in its series Computing in Economics and Finance 2002 with number 200.
Date of creation: 01 Jul 2002
Date of revision:
Neural networks; Genetic algorithms; Bounded rationality; learning; expectations; innovation dynamics;
Other versions of this item:
- Murat Yildizoglu, 2001. "Connecting adaptive behaviour and expectations in models of innovation: The Potential Role of Artificial Neural Networks," Working Papers 2001-2, Equipe Industries Innovation Institutions, Université Bordeaux IV, France.
- O3 - Economic Development, Technological Change, and Growth - - Technological Change; Research and Development; Intellectual Property Rights
- D21 - Microeconomics - - Production and Organizations - - - Firm Behavior: Theory
- D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search, Learning, and Information
This paper has been announced in the following NEP Reports:
- NEP-ALL-2003-10-20 (All new papers)
- NEP-CBE-2003-10-20 (Cognitive & Behavioural Economics)
- NEP-CMP-2003-10-20 (Computational Economics)
- NEP-INO-2003-10-20 (Innovation)
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.:
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"Recognizing Investment Opportunities at the Onset of Recoveries,"
Modeling, Computing, and Mastering Complexity 2003
07, Society for Computational Economics.
- Fioretti, Guido, 2006. "Recognising investment opportunities at the onset of recoveries," Research in Economics, Elsevier, vol. 60(2), pages 69-84, June.
- Guido Fioretti, 2002. "Recognizing Investment Opportunities at the Onset of Recoveries," Macroeconomics 0207008, EconWPA.
- Murat YILDIZOGLU (GREQAM, CNRS, UMR 6579) & Marc-Alexandre SENEGAS (GREThA, CNRS, UMR 5113) & Isabelle SALLE (GREThA, CNRS, UMR 5113) & Martin ZUMPE (GREThA, CNRS, UMR 5113), 2011.
"Learning the optimal buffer-stock consumption rule of Carroll,"
Cahiers du GREThA
2011-11, Groupe de Recherche en Economie Théorique et Appliquée.
- Murat Yildizoglu & Marc-Alexandre Sénégas & Isabelle Salle & Martin Zumpe, 2011. "Learning the optimal buffer-stock consumption rule of Carroll," Working Papers halshs-00573689, HAL.
- Murat YILDIZOGLU (Université Aix-Marseille3), 2009. "Evolutionary approaches of economic dynamics (In French)," Cahiers du GREThA 2009-16, Groupe de Recherche en Economie Théorique et Appliquée.
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