Evolution of communication using symbol combination in populations of neural networks

Research output: Contribution to conferencePaperpeer-review

Abstract

This paper uses a model of neural network and genetic algorithms to simulate the evolution of communication in populations of evolving neural networks. It focuses on the emergence of simple forms of syntax, i.e., the combination of two symbols. The simulation task resembles Savage-Rumbaugh and Rumbaugh's experiment (1978) on ape language and symbol acquisition. The simulation results show the evolution and cultural transmission of languages based on combination of grounded symbols. The model is analyzed according to the issues of the symbol grounding and symbol acquisition problems
Original languageEnglish
Pages4365
DOIs
Publication statusPublished - Jul 1999

Keywords

  • biocybernetics
  • evolution (biological)
  • genetic algorithms
  • neural nets
  • physiological models
  • communication
  • cultural transmission
  • evolution
  • neural network
  • symbol acquisition
  • symbol grounding
  • syntax

Fingerprint

Dive into the research topics of 'Evolution of communication using symbol combination in populations of neural networks'. Together they form a unique fingerprint.

Cite this