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A Hybrid Model for Learning Word-Meaning Mappings

  • Federico Divina
  • Paul Vogt
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4211)

Abstract

In this paper we introduce a model for the simulation of language evolution, which is incorporated in the New Ties project. The New Ties project aims at evolving a cultural society by integrating evolutionary, individual and social learning in large scale multi-agent simulations. The model presented here introduces a novel implementation of language games, which allows agents to communicate in a more natural way than with most other existing implementations of language games. In particular, we propose a hybrid mechanism that combines cross-situational learning techniques with more informed feedback mechanisms. In our study we focus our attention on dealing with referential indeterminacy after joint attention has been established and on whether the current model can deal with larger populations than previous studies involving cross-situational learning. Simulations show that the proposed model can indeed lead to coherent languages in a quasi realistic world environment with larger populations.

Keywords

Hybrid Model Joint Attention Perceptual Feature Language Game Association Score 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Federico Divina
    • 1
  • Paul Vogt
    • 1
    • 2
  1. 1.Induction of Linguistic Knowledge / Language and Information ScienceTilburg UniversityTilburgThe Netherlands
  2. 2.Language Evolution and Computation Research Unit, School of Philosophy, Psychology and Language SciencesUniversity of EdinburghUK

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