CFP last date
22 April 2024
Reseach Article

Modeling a Honeybee using Spiking Neural Network to Simulate Nectar Reporting Behavior

by Subha Fernando, Nishantha Kumarasinghe
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 130 - Number 8
Year of Publication: 2015
Authors: Subha Fernando, Nishantha Kumarasinghe
10.5120/ijca2015907078

Subha Fernando, Nishantha Kumarasinghe . Modeling a Honeybee using Spiking Neural Network to Simulate Nectar Reporting Behavior. International Journal of Computer Applications. 130, 8 ( November 2015), 32-39. DOI=10.5120/ijca2015907078

@article{ 10.5120/ijca2015907078,
author = { Subha Fernando, Nishantha Kumarasinghe },
title = { Modeling a Honeybee using Spiking Neural Network to Simulate Nectar Reporting Behavior },
journal = { International Journal of Computer Applications },
issue_date = { November 2015 },
volume = { 130 },
number = { 8 },
month = { November },
year = { 2015 },
issn = { 0975-8887 },
pages = { 32-39 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume130/number8/23233-2015907078/ },
doi = { 10.5120/ijca2015907078 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:24:55.573871+05:30
%A Subha Fernando
%A Nishantha Kumarasinghe
%T Modeling a Honeybee using Spiking Neural Network to Simulate Nectar Reporting Behavior
%J International Journal of Computer Applications
%@ 0975-8887
%V 130
%N 8
%P 32-39
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Swarm cognition is the field that explores the possibility of implanting human cognitive functions on machines by transplanting the processes in naturally self-organized colonies. These natural colonies, especially ant colony, honey bee colony, etc, have been deeply studied to explore the factors which enable them to simulate high cognitive functions, such as decision making, labor division, etc. In swarm cognition a human neuron is matched to an ant or a honeybee in a colony, because both have limited capabilities and their reactions mainly depend only on local interactions with their neighbors. This paper has postulated that any individual in a swarm is itself a network of neurons and thereby swarm is a network of networks. Each child network react to its neighboring networks such a way that where the mother network will be enabled to respond appropriately to the environmental changes. Accordingly, the paper models a honeybee as a network of neurons. The basic model is evaluated by simulating the behavior that a honeybee generates when it reports the food sources to the colony members. A neuron was modeled as a spiking neuron and the network consists of excitatory and inhibitory spiking neurons. The results have demonstrated that the proposed model is capable of demonstrating food reporting process of a honeybee.

References
  1. Trianni V. and Tusi E. 2011 Swarm Cognition and Artificial Life, Advances in Artificial Life. Darwin Meets von Neumann, Lecture Notes in Computer Science:5778:270-277
  2. Ahmed H. and Glasgow J. 2012 Swarm Intelligence: Concepts, Models and Applications, Technical Report 2012-585, School of Computing, Queen's University, Canada.
  3. Blum C. 2005 Ant colony optimization: Introduction and recent trends, Physics of Life Reviews 2 (2005) 353–373.
  4. Karaboga D. and Akay B. 2009 A Survey: Algorithms Simulating Bee Swarm Intelligence; Artificial Intelligence Review; 31 (1), pp. 68-85.
  5. Krink T. Swarm Intelligence - Introduction , EVALife Group, Department of Computer Science, University of Aarhus.
  6. Myerscough M.R. 2003 Dancing for a decision: a matrix model for nest-site choice by honeybees, Proc. R. Soc. Lond. 270(1515)577-582.
  7. Bailis P., Nagpal R. and Werfel J. 2010 Positional Communication and Private Information in Honeybee Foraging Models, in Swarm Intelligence, Eds. Springer Berlin Heidelberg, pp. 263–274.
  8. Trianni V., Tusi E., Passino, E.M., Marshell J.A.R. 2011 Swarm Cognition: an interdisciplinary approach to the study of self-organizing biological collectives, Swarm Intelligence:5:3-18.
  9. Abbott L.F. and Nelson S.B 2000 Synaptic Plasticity: taming the beast, Neuroscience, vol.3.pp.1178-1183.
  10. Izhikevich E.M., Dynamical Systems in Neuroscience: The geometry of excitability and bursting, 2007 , chapter 8.
  11. Gil M. 2010 Reward expectations in honeybees, Communicative & Integrative Biology 3:2, 95-100.
  12. Seeley T.D., Mikheyev A. S., and Pagano G. J. 2000 Dancing bees tune both duration and rate of waggle-run production in relation to nectar-source profitability, J. Comp. Physiol. [A], vol. 186, no. 9, pp. 813–819.
  13. Yahya H. The miracle of the Honeybee 2007, chapter 2-3.
  14. Thom C 2003 The tremble dance of honey bees can be caused by hive-external foraging experience, J. Exp. Biol., vol. 206, no. Pt 13, pp. 2111–2116.
  15. Seeley T.D. 1992 The tremble dance of the honey bee: message and meanings, Behav. Ecol. Sociobiol., vol. 31, no. 6, pp. 375–383.
  16. Passino K.M. and Seeley T.D. 2006 Modeling and analysis of nest-site selection by honeybee swarms: the speed and accuracy trade-off, Behav. Ecol. Sociobiol., vol. 59, no. 3, pp. 427–442.
  17. Seeley T. D. 1994 Honey bee foragers as sensory units of their colonies, Behav. Ecol. Sociobiol., vol. 34, no. 1, pp. 51–62.
  18. Michener C.D.  1974. The social behavior of the bees: a comparative study. Harvard Univ. Press., Cambridge, Mass
  19. Tautz J1, Maier S, Groh C, Rossler W, Brockmann A. 2003. Behavioral performance in adult honey bees is influenced by the temperature experienced during their pupal development. Proc Natl Acad Sci U S A. 2003 Jun 10;100(12):7343-7.
  20. Sinakevitch I, Mustard JA, Smith BH. 2011. Distribution of the octopamine receptor AmOA1 in the honey bee brain. PLoS One. 6(1):e14536. doi: 10.1371/journal.pone.0014536.
  21. Izhikevich E.M., 2003. Simple Model of Spiking Neurons. IEEE Transactions on Neural Networks, vol. 14, no. 6, pp. 1569-1572.
  22. Quintavalle.A, 2013, Voltage-Gated Calcium Channels in Honey Bees: Physiological Roles and Potential Targets for Insecticides,BioSciences Master Reviews, pp.1-11.
  23. Perk C.G. and Mercer A.R., 2006, Dopamine Modulation of Honey Bee (Apis mellifera) Antennal-Lobe Neurons, Journal of Neurophysiol, vol 95. pp. 1147–1157.
Index Terms

Computer Science
Information Sciences

Keywords

Swarm Cognition Spiking Neurons Honeybee Foraging