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Related Experiment Videos

Language evolution and information theory.

J B Plotkin1, M A Nowak

  • 1Institut for Advanced Study, Princeton, NJ, 08540, USA. plotkin@ias.edu

Journal of Theoretical Biology
|June 22, 2000
PubMed
Summary
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Language evolution models show that signal errors create a fitness limit. Word formation overcomes this by increasing word length, exponentially boosting language fitness, similar to noisy coding theorems.

Area of Science:

  • Information theory
  • Evolutionary linguistics
  • Computational linguistics

Background:

  • Models of language evolution often focus on signal transmission.
  • Understanding how signals acquire meaning is crucial for language development.
  • The probability of signal confusion can limit a language's effectiveness.

Purpose of the Study:

  • To place language evolution models within an information theory framework.
  • To investigate the relationship between signal error, meaning association, and language fitness.
  • To explore how word formation impacts language evolution and overcome inherent limitations.

Main Methods:

  • Utilizing information theory principles to model language evolution.
  • Developing a general mathematical model for word formation.

Related Experiment Videos

  • Analyzing the impact of signal error probability on language fitness.
  • Connecting the derived error limit to Shannon's noisy coding theorem.

    • Main Results:

    • A probability of mistaking signals for each other imposes an error limit on language fitness.
    • Increasing the number of signals does not indefinitely improve language fitness.
    • Word formation allows for a linear increase in word length to achieve an exponential increase in maximum fitness.
    • The study demonstrates a direct connection between the language error limit and Shannon's noisy coding theorem.

    Conclusions:

    • Language evolution is constrained by signal error, establishing a fitness ceiling.
    • Word formation is a key mechanism for enhancing language capacity beyond this error limit.
    • The findings provide a theoretical framework linking information theory to the evolution of complex communication systems.