Abstract
Some economists who have relied on the rational expectations hypothesis are now seeking to demonstrate that rational expectations equilibria can emerge in models with agents who are artificially intelligent. They typically model agents’ intelligence through the use of genetic algorithms. However, these algorithms misrepresent current understanding of human cognition as well as well-known and long-standing evidence from business history and the history of technology. This paper implements a well-validated representation of human cognition in SDML, a logic-based programming language that is optimised for representations of interactions among agents. Within that software environment, a model of a transition economy is developed with three production sectors and a household sector. The numerical outputs from that model are broadly in accord with the statistical evidence from the Russian economy. The model itself is developed explicitly to incorporate qualitatively specified characteristics of entrepreneurial behaviour in that economy. Unlike conventional economic models, transactions are negotiated and effected explicitly — there are no unspecified or under-specified “markets”.
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Moss, S., Sent, EM. (1999). Boundedly Versus Procedurally Rational Expectations. In: Hallett, A.H., McAdam, P. (eds) Analyses in Macroeconomic Modelling. Advances in Computational Economics, vol 12. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-5219-2_5
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DOI: https://doi.org/10.1007/978-1-4615-5219-2_5
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