Investment behavior under Knightian uncertainty - An evolutionary approach

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@Article{Lensberg:1999:JEDC,

• author = "Terje Lensberg",
• title = "Investment behavior under Knightian uncertainty - An evolutionary approach",
• journal = "Journal of Economic Dynamics and Control",
• year = "1999",
• volume = "23",
• pages = "1587--1604",
• number = "9-10",
• owner = "wlangdon",
• URL = "http://www.sciencedirect.com/science/article/B6V85-3Y9RKX5-G/2/6c6369b7934fdea4d1937c49a35ada38",
• keywords = "genetic algorithms, genetic programming, Knightian uncertainty, Bayesian rationality",
• URL = "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.205.7821",
• URL = "http://sci2s.ugr.es/keel/pdf/specific/articulo/science2_31.pdf",
• DOI = "doi:10.1016/S0165-1889(98)00085-2",
• abstract = "The as if view of economic rationality defends the profit maximisation hypothesis by pointing out that only those firms who act as if they maximise profits can survive in the long run. Recently, the problem of arriving at a logically consistent definition of rational behaviour in games has shown that one must sometimes study explicitly the evolutionary processes that form the basis of this view. The purpose of this paper is to investigate the usefulness of genetic programming as a tool for generating hypotheses about rational behavior in situations where explicit maximization is not well defined. We use an investment decision problem with Knightian uncertainty as a borderline test case, and show that when the artificial agents receive the same information about the unknown probability distributions, they develop behaviour rules as if they were expected utility maximisers with Bayesian learning rules.",
• notes = "JEL classification codes: B41; C63; D83",

}

Genetic Programming entries for Terje Lensberg

Citations