Spike response threshold model for task allocation in multi-agent systems

Wonki Lee, Dae Eun Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

This paper focuses on task allocation problem in multi-agent system and we consider the solution for regulating the proportion of groups performing tasks equally to the proportion of task demands. The response threshold model inspired by division of labor observed in insect societies is applied. Each agent converts the information from surrounding environment to the spike and decides its task based on the response threshold model. The decision of an agent has partial control over its environment, but the overall system shows a desired performance. The algorithm is implemented using simulated robots and demonstrates its adaptivity with changes for task demands and the number of agents in a group.

Original languageEnglish
Title of host publicationRO-MAN 2017 - 26th IEEE International Symposium on Robot and Human Interactive Communication
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1165-1168
Number of pages4
ISBN (Electronic)9781538635186
DOIs
Publication statusPublished - 2017 Dec 8
Event26th IEEE International Symposium on Robot and Human Interactive Communication, RO-MAN 2017 - Lisbon, Portugal
Duration: 2017 Aug 282017 Sep 1

Publication series

NameRO-MAN 2017 - 26th IEEE International Symposium on Robot and Human Interactive Communication
Volume2017-January

Other

Other26th IEEE International Symposium on Robot and Human Interactive Communication, RO-MAN 2017
Country/TerritoryPortugal
CityLisbon
Period17/8/2817/9/1

Bibliographical note

Funding Information:
ACKNOWLEDGMENT This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MEST) (No. 2014R1A2A1A11053839).

Publisher Copyright:
© 2017 IEEE.

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Human-Computer Interaction
  • Control and Optimization

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