Connecting adaptive behaviour and expectations in models of innovation: The Potential Role of Artificial Neural Networks

Murat Yildizoglu ()

Working Papers from Equipe Industries Innovation Institutions, Université Bordeaux IV, France

Abstract: In 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).

Keywords: Neural networks; Genetic algorithms; Bounded rationality; learning; expectations; innovation dynamics. (search for similar items in EconPapers)
JEL-codes: L1 D83 D84 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-cmp, nep-ent, nep-evo, nep-ino, nep-mic, nep-net and nep-tid
Date: 2001
View citations in EconPapers

Downloads: (external link)
http://beagle.u-bordeaux4.fr/ifrede/e3i/publications/2001/2001-2.pdf (application/pdf)
Our link check indicates that this URL is bad, the error code is: 404 Not Found

Related works:
Working Paper: Connecting adaptive behaviour and expectations in models of innovation: The Potential Role of Artificial Neural Networks (2002)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: http://EconPapers.repec.org/RePEc:iii:wpeiii:2001-2

Access Statistics for this paper

More papers in Working Papers from Equipe Industries Innovation Institutions, Université Bordeaux IV, France
Contact information at EDIRC.
Series data maintained by Vincent Frigant ().