Analysis of task allocation based on social utility and incompatible individual preference

Naoki Iijima, Masashi Hayano, Ayumi Sugiyama, Toshiharu Sugawara

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

5 Citations (Scopus)

Abstract

This paper proposes a task allocation method in which, although social utility is attempted to be maximized, agents also give weight to individual preferences based on their own specifications and capabilities. Due to the recent advances in computer and network technologies, many services can be provided by appropriately combining multiple types of information and different computational capabilities. The tasks that are carried out to perform these services are executed by allocating them to appropriate agents, which are computational entities having specific functionalities. However, these tasks are huge and appear simultaneously, and task allocation is thus a challenging issue since it is a combinatorial problem. The proposed method, which is based on our previous work, allocates resources/tasks to the appropriate agents by taking into account both social utility and individual preferences. We experimentally demonstrate that the appropriate strategy to decide the preference depends on the type of task and the features of the reward function as well as the social utility.

Original languageEnglish
Title of host publicationTAAI 2016 - 2016 Conference on Technologies and Applications of Artificial Intelligence, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages24-31
Number of pages8
ISBN (Electronic)9781509057320
DOIs
Publication statusPublished - 2017 Mar 16
Event2016 Conference on Technologies and Applications of Artificial Intelligence, TAAI 2016 - Hsinchu, Taiwan, Province of China
Duration: 2016 Nov 252016 Nov 27

Publication series

NameTAAI 2016 - 2016 Conference on Technologies and Applications of Artificial Intelligence, Proceedings

Other

Other2016 Conference on Technologies and Applications of Artificial Intelligence, TAAI 2016
CountryTaiwan, Province of China
CityHsinchu
Period16/11/2516/11/27

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Control and Optimization
  • Information Systems

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  • Cite this

    Iijima, N., Hayano, M., Sugiyama, A., & Sugawara, T. (2017). Analysis of task allocation based on social utility and incompatible individual preference. In TAAI 2016 - 2016 Conference on Technologies and Applications of Artificial Intelligence, Proceedings (pp. 24-31). [7880161] (TAAI 2016 - 2016 Conference on Technologies and Applications of Artificial Intelligence, Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/TAAI.2016.7880161