Asynchronous agent teams for collaborative tasks based on bottom-up alliance formation and adaptive behavioral strategies

Masashi Hayano, Naoki Iijima, Toshiharu Sugawara

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

    1 Citation (Scopus)

    Abstract

    This paper proposes a method to efficiently form teams for tasks that can be executed by multiple agents with different capabilities in a distributed network environment. Recent growing information and networking technologies have been realizing new types of computerized services that have been achieved by appropriately combining data from networked sensing devices and actuators controlled by intelligent programs in decentralized environments. Because these types of services can be realized by a team of agents acting using their own capabilities, how such teams can be formed effectively and efficiently in a distributed environment in a bottom-up manner is a key issue for autonomic computing. Our proposed method can autonomously recognize the dependable agents based on past successful cooperative behaviors, and they generate a tight alliance structure to execute the given tasks. Such an alliance structure avoids some conflicts by preventing many tasks being allocated to a few capable agents. We experimentally show that the proposed method can stably exhibit good performance and can adapt to environmental changes where task structure varies.

    Original languageEnglish
    Title of host publicationProceedings - 2017 IEEE 15th International Conference on Dependable, Autonomic and Secure Computing, 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing, 2017 IEEE 3rd International Conference on Big Data Intelligence and Computing and 2017 IEEE Cyber Science and Technology Congress, DASC-PICom-DataCom-CyberSciTec 2017
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages589-596
    Number of pages8
    Volume2018-January
    ISBN (Electronic)9781538619551
    DOIs
    Publication statusPublished - 2018 Mar 29
    Event15th IEEE International Conference on Dependable, Autonomic and Secure Computing, 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing, 2017 IEEE 3rd International Conference on Big Data Intelligence and Computing and 2017 IEEE Cyber Science and Technology Congress, DASC-PICom-DataCom-CyberSciTec 2017 - Orlando, United States
    Duration: 2017 Nov 62017 Nov 11

    Other

    Other15th IEEE International Conference on Dependable, Autonomic and Secure Computing, 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing, 2017 IEEE 3rd International Conference on Big Data Intelligence and Computing and 2017 IEEE Cyber Science and Technology Congress, DASC-PICom-DataCom-CyberSciTec 2017
    CountryUnited States
    CityOrlando
    Period17/11/617/11/11

    Keywords

    • Allocation problem
    • Multi-agent systems
    • Reciprocity
    • Reinforcement learning
    • Structuring

    ASJC Scopus subject areas

    • Safety, Risk, Reliability and Quality
    • Health Informatics
    • Artificial Intelligence
    • Computer Networks and Communications
    • Hardware and Architecture
    • Computer Science Applications
    • Information Systems

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  • Cite this

    Hayano, M., Iijima, N., & Sugawara, T. (2018). Asynchronous agent teams for collaborative tasks based on bottom-up alliance formation and adaptive behavioral strategies. In Proceedings - 2017 IEEE 15th International Conference on Dependable, Autonomic and Secure Computing, 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing, 2017 IEEE 3rd International Conference on Big Data Intelligence and Computing and 2017 IEEE Cyber Science and Technology Congress, DASC-PICom-DataCom-CyberSciTec 2017 (Vol. 2018-January, pp. 589-596). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/DASC-PICom-DataCom-CyberSciTec.2017.105