Using Neural Networks to Model Bounded Rationality in Interactive Decision-Making
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.
When requesting a correction, please mention this item's handle: RePEc:cam:camdae:0339. 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: (Jake Dyer)
If references are entirely missing, you can add them using this form.