Stratified Constraint Satissfaction Networks in Synergetic Multi-Agent Simulations of Language Evolution

Stratified Constraint Satissfaction Networks in Synergetic Multi-Agent Simulations of Language Evolution

Alexander Mehler (Bielefeld University, Germany)
Copyright: © 2007 |Pages: 36
DOI: 10.4018/978-1-59904-111-7.ch005
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Abstract

We describe a simulation model of language evolution which integrates synergetic linguistics with multi-agent modelling. On the one hand, this enables the utilization of knowledge about the distribution of the parameter values of system variables as a touch stone of simulation validity. On the other hand, it accounts 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 self-regulation and self-organization in mechanisms of (dialogically aligned) language learning. Consequently, the simulation model includes four level, (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 modelling 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.

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