Token-based autonomous task allocation in flocking systems

Andras Kokuti, V. Simon, Bernat Wiandt

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

1 Citation (Scopus)

Abstract

There are serious contributions to the theoretical foundations of flocking systems, but there are only few systems which have the capability of autonomous task allocation, however, many use cases demand this functionality. The implementation of a task allocation algorithm could be a serious challenge even in a simulated environment due to the numerous problems arising from the nature of these systems. This paper proposes a novel algorithm to find the optimal allocation of heterogeneous agents to heterogeneous tasks by utilizing distributed auctions based on local peer-To-peer wireless communication and exploiting graph theory with a tree-based multicast protocol. The solution was tested over a number of different scenarios and compared to existing algorithms in order to measure and prove its capability in handling autonomous task allocation in different systems as well.

Original languageEnglish
Title of host publicationProceedings of the 2016 Federated Conference on Computer Science and Information Systems, FedCSIS 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1461-1466
Number of pages6
ISBN (Electronic)9788360810903
DOIs
Publication statusPublished - Nov 3 2016
Event2016 Federated Conference on Computer Science and Information Systems, FedCSIS 2016 - Gdansk, Poland
Duration: Sep 11 2016Sep 14 2016

Other

Other2016 Federated Conference on Computer Science and Information Systems, FedCSIS 2016
CountryPoland
CityGdansk
Period9/11/169/14/16

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems
  • Computer Science (miscellaneous)

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  • Cite this

    Kokuti, A., Simon, V., & Wiandt, B. (2016). Token-based autonomous task allocation in flocking systems. In Proceedings of the 2016 Federated Conference on Computer Science and Information Systems, FedCSIS 2016 (pp. 1461-1466). [7733444] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.15439/2016F424