A publish-subscribe based architecture for testing multiagent systems

Nathalia Moraes Do Nascimento, Carlos Juliano Moura Viana, Arndt Von Staa, Carlos José Pereira De Lucena

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

    6 Scopus citations

    Abstract

    Multiagent systems (MASs) have been applied to several application domains, such as e-commerce, unmanned vehicles, and many others. In addition, a set of different techniques has been integrated into multiagent applications. However, few of these applications have been commercially deployed and few of these techniques have been fully exploited by industrial applications. One reason is the lack of procedures guaranteeing that multiagent systems would behave as desired. Most of the existing test approaches only test agents as single individuals and do not provide ways of inspecting the behavior of an agent as part of a group, and the behavior of the whole group of agents. Accordingly, we modeled and developed a publishsubscribe- based architecture to facilitate the implementation of systems to test MASs at the agent and group levels. To illustrate and evaluate the use of the proposed architecture, we developed an MAS-based application and performed functional and performance ad-hoc tests.

    Original languageEnglish (US)
    Title of host publicationProceedings - SEKE 2017
    Subtitle of host publication29th International Conference on Software Engineering and Knowledge Engineering
    PublisherKnowledge Systems Institute Graduate School
    Pages521-526
    Number of pages6
    ISBN (Electronic)1891706411
    DOIs
    StatePublished - 2017
    Event29th International Conference on Software Engineering and Knowledge Engineering, SEKE 2017 - Pittsburgh, United States
    Duration: Jul 5 2017Jul 7 2017

    Publication series

    NameProceedings of the International Conference on Software Engineering and Knowledge Engineering, SEKE
    ISSN (Print)2325-9000
    ISSN (Electronic)2325-9086

    Conference

    Conference29th International Conference on Software Engineering and Knowledge Engineering, SEKE 2017
    Country/TerritoryUnited States
    CityPittsburgh
    Period7/5/177/7/17

    All Science Journal Classification (ASJC) codes

    • Software

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