A Markov analysis of social learning and adaptation

dc.contributor.authorWheeler, S.
dc.contributor.authorBean, N.
dc.contributor.authorGaffney, J.
dc.contributor.authorTaylor, P.
dc.date.issued2006
dc.descriptionThe original publication is available at www.springerlink.com
dc.description.abstractA number of recent contributions to the literature have modelled social learning and adaptation in an economic context. Understanding the processes driving these models is important in order to explain and predict the behaviour of the economy. In this paper, we analyze the economic applications for a class of adaptive learning models with bounded rational agents. The dynamics of these economies can be thought of as arising from discrete-time Markov chains. In particular, conditions for uniqueness of equilibria, convergence and stability in the economic systems follow from the accessibility and communication structures of these Markov chains. We establish a correspondence between absorbing states of the Markov chains and economic equilibria, whether stable or unstable, and develop theorems giving conditions for absorption and recurrence. Furthermore, we develop practical applications of these theorems using a cobweb model. We use a genetic algorithm, operating under election, as an example of a well known adaptive learning process.
dc.description.statementofresponsibilityScott Wheeler, Nigel Bean, Janice Gaffney and Peter Taylor
dc.identifier.citationJournal of Evolutionary Economics, 2006; 16(3):299-319
dc.identifier.doi10.1007/s00191-006-0017-5
dc.identifier.issn0936-9937
dc.identifier.issn1432-1386
dc.identifier.orcidBean, N. [0000-0002-5351-3104]
dc.identifier.urihttp://hdl.handle.net/2440/23807
dc.language.isoen
dc.publisherSpringer-Verlag
dc.source.urihttp://www.springerlink.com/content/524547g6j0327676/
dc.subjectadaptive learning
dc.subjectMarkov chain
dc.subjectcobweb model
dc.titleA Markov analysis of social learning and adaptation
dc.typeJournal article
pubs.publication-statusPublished

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