Understanding linguistic evolution by visualizing the emergence of topographic mappings

Henry Brighton, Simon Kirby

Research output: Contribution to journalArticleScientificpeer-review

9 Citations (Scopus)

Abstract

We show how cultural selection for learnability during the process of linguistic evolution can be visualized using a simple iterated learning model. Computational models of linguistic evolution typically focus on the nature of, and conditions for, stable states. We take a novel approach and focus on understanding the process of linguistic evolution itself. What kind of evolutionary system is this process? Using visualization techniques, we explore the nature of replicators in linguistic evolution, and argue that replicators correspond to local regions of regularity in the mapping between meaning and signals. Based on this argument, we draw parallels between phenomena observed in the model and linguistic phenomena observed across languages. We then go on to identify issues of replication and selection as key points of divergence in the parallels between the processes of linguistic evolution and biological evolution.

Original languageEnglish
Pages (from-to)229-42
Number of pages14
JournalArtificial Life
Volume12
Issue number2
DOIs
Publication statusPublished - 2006
Externally publishedYes

Keywords

  • Artificial Intelligence
  • Biological Evolution
  • Culture
  • Gene Expression
  • Humans
  • Language
  • Learning
  • Linguistics
  • Models, Theoretical
  • Visual Perception

Fingerprint Dive into the research topics of 'Understanding linguistic evolution by visualizing the emergence of topographic mappings'. Together they form a unique fingerprint.

  • Cite this