Using Neural Networks to Model Bounded Rationality in Interactive Decision-Making
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Authors
Sgroi, Daniel
Publication Date
2004-06-16Series
Cambridge Working Papers in Economics
Publisher
Faculty of Economics
Language
en_GB
Type
Working Paper
Metadata
Show full item recordCitation
Sgroi, D. (2004). Using Neural Networks to Model Bounded Rationality in Interactive Decision-Making. https://doi.org/10.17863/CAM.4996
Abstract
This paper considers the use of neural networks to model bounded rational behaviour. The underlying theory and use of neural networks is now a component of various forms of scientific enquiry, be it modelling artificial intelligence, developing better pattern recognition or solving complex optimization problems. This paper surveys the recent literature in economics on their use as a plausible model of learning by example, in which the focus is not on improving their ability to perform to the point of zero error, but rather examining the sorts of errors they make and comparing these with observed bounded rational behaviour.
Keywords
Classification-JEL: C72, D00, D83, neural networks, bounded rationality, learning, repeated games, industrial organization
Identifiers
This record's DOI: https://doi.org/10.17863/CAM.4996
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