A self-configurable IoT agent system based on environmental variability

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

    4 Scopus citations

    Abstract

    This thesis develops a self-configurable system to design agents for Internet of Things (IoT) applications. The proposed approach goes beyond existing methods by supporting handling variability in IoT agents according to environmental changes. As part of the research, we have designed a software framework, prototyped several IoT applications, and conducted simulation and machine learning experiments. We find that (1) IoT agents vary according to the physical, software behavior and analysis architecture; (2) the configuration of the set of agents can be adjusted and reconfigured through feedback evaluative machine learning; and (3) reconfiguring a set of agents dynamically in accordance with environmental variants leads to better performance.

    Original languageEnglish (US)
    Title of host publication17th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2018
    PublisherInternational Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
    Pages1761-1763
    Number of pages3
    ISBN (Print)9781510868083
    StatePublished - 2018
    Event17th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2018 - Stockholm, Sweden
    Duration: Jul 10 2018Jul 15 2018

    Publication series

    NameProceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS
    Volume3
    ISSN (Print)1548-8403
    ISSN (Electronic)1558-2914

    Other

    Other17th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2018
    Country/TerritorySweden
    CityStockholm
    Period7/10/187/15/18

    All Science Journal Classification (ASJC) codes

    • Artificial Intelligence
    • Software
    • Control and Systems Engineering

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