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Abstract

We describe a simulation model of language evolution which integrates synergetic linguistics with multi-agent modeling. On the one hand, this enables to utilize knowledge about the distribution of the parameter values of system variables as a touch stone of simulation validity. On the other hand it allows to account for synergetic interdependencies of microscopic system variables and macroscopic order parameters. This approach goes beyond the classical setting of synergetic linguistics by grounding processes of selfregulation and -organization in mechanisms of (dialogically aligned) language learning. Consequently, the simulation model includes four levels, that are, (i) the level of single information processing agents which are (ii) dialogically aligned in communication processes enslaved (iii) by the social system in which the agents participate and whose countless communication events shape (iv) the corresponding language system. In summary, the present paper is basically conceptual. It outlines a simulation model which bridges between different levels of language modeling kept apart in contemporary simulation models. This model relates to artificial cognition systems in the sense that it may be implemented to endow an artificial agent community in order to perform distributed processes of meaning constitution.

@incollection{mehler06stratified,
  author={Alexander Mehler},
  title={Stratified Constraint Satisfaction Networks in Synergetic Multi-Agent Simulations of Language Evolution},
  year={2006},
  pages={140-174},
  address={Hershey},
  editor={Angelo Loula and Ricardo Gudwin and Joao Queiroz},
  publisher={Idea Group Inc.},
  booktitle={Artificial Cognition Systems},
  url={http://www.isrl.uiuc.edu/~amag/langev/paper/mehler06stratified.html}
}

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