Translating the dances of honeybees into resource location

Research output: Chapter in Book/Report/Conference proceedingChapter

3 Citations (Scopus)

Abstract

Dance communication of honeybees has been well known since von Frisch's work. Many researchers have believed that the waggle dance of forager bees shows the direction and distance of resources. In this paper, we suggest a possibility that dance followers employ a temporal path integration mechanism to translate the dance. We apply a neural network model consisting of sinusoidal arrays for a representation of the resource vector. The followers keeping in contact with the forager accumulate the activation of head direction relative to a gravity compass and calculate the resource vector in a circular array of neurons. This provides an idea of how bees can translate the sickle dance as well as the waggle dance into the resource location. The neural model is tested with simulated robots to communicate the resource location.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsXin Yao, John A. Bullinaria, Jonathan Rowe, Peter Tino, Ata Kaban, Edmund Burke, Jose A. Lozano, Jim Smith, Juan J. Merelo-Guervos, Hans-Paul Schwefel
PublisherSpringer Verlag
Pages962-971
Number of pages10
ISBN (Print)3540230920, 9783540230922
DOIs
Publication statusPublished - 2004

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3242
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Kim, D. (2004). Translating the dances of honeybees into resource location. In X. Yao, J. A. Bullinaria, J. Rowe, P. Tino, A. Kaban, E. Burke, J. A. Lozano, J. Smith, J. J. Merelo-Guervos, & H-P. Schwefel (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 962-971). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3242). Springer Verlag. https://doi.org/10.1007/978-3-540-30217-9_97