Lexicon Convergence in a Population With and Without Metacommunication

  • Zoran Macura
  • Jonathan Ginzburg
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4211)


How does a shared lexicon arise in population of agents with differing lexicons, and how can this shared lexicon be maintained over multiple generations? In order to get some insight into these questions we present an ALife model in which the lexicon dynamics of populations that possess and lack metacommunicative interaction (MCI) capabilities are compared. We suggest that MCI serves as a key component in the maintenance of a linguistic interaction system. We ran a series of experiments on mono-generational and multi-generational populations whose initial state involved agents possessing distinct lexicons. These experiments reveal some clear differences in the lexicon dynamics of populations that acquire words solely by introspection contrasted with populations that learn using MCI or using a mixed strategy of introspection and MCI. Over a single generation the performance between the populations with and without MCI is comparable, in that the lexicon converges and is shared by the whole population. In multi-generational populations lexicon diverges at a faster rate for an introspective population, eventually consisting of one word being associated with every meaning, compared with MCI capable populations in which the lexicon is maintained, where every meaning is associated with a unique word.


Adult Agent Hybrid Population Association Score Conversational Interaction Infant Agent 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Zoran Macura
    • 1
  • Jonathan Ginzburg
    • 1
  1. 1.Department of Computer ScienceKing’s College, LondonLondon

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