Full-text

|| Go to publishers' web page for final fulltext/PDF. (see the Authoritative link as below)

URL: http://www.ling.ed.ac.uk/~kenny/publicat...language_final.ps.gz

Related links

Authoritative: http://www.springerlink.com/link.asp?id=uxcn3rmmgfx5p2ck   (Publisher's PDF... likely be available here.)

Source: http://www.ling.ed.ac.uk/~kenny/publications.html

CiteSeer: http://citeseer.ist.psu.edu/565681.html

Web search: Google Web Search   ::   Google Scholar

Within this site: Cited by (10)    References (15)

Abstract

Models of the cultural evolution of language typically assume a very simplified population dynamic. In the most common modelling framework (the Iterated Learning Model) populations are modelled as consisting of a series of non-overlapping generations, with each generation consisting of a single agent. However, the literature on language birth and language change suggests that population dynamics play an important role in real-world linguistic evolution. We aim to develop computational models to investigate this interaction between population factors and language evolution. Here we present results of extending a well-known Iterated Learning Model to a population model which involves multiple individuals. This extension reveals problems with the model of grammar induction, but also shows that the fundamental results of Iterated Learning experiments still hold when we consider an extended population model.

@inproceedings{smithHurford03ECAL,
  author={K. Smith and J. Hurford},
  title={Language Evolution in Populations: extending the Iterated Learning Model},
  year={2003},
  pages={507-516},
  booktitle={ECAL03},
  url={http://groups.lis.illinois.edu/amag/langev/paper/smithHurford03ECAL.html}
}