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    Incorporating Change Management Within Dynamic Requirements-Based Model-Driven Agent Development

    Access Status
    Fulltext not available
    Authors
    Goncalves, J.
    Krishna, Aneesh
    Date
    2017
    Type
    Journal Article
    
    Metadata
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    Citation
    Goncalves, J. and Krishna, A. 2017. Incorporating Change Management Within Dynamic Requirements-Based Model-Driven Agent Development. The Computer Journal. 6 (7): pp. 1045-1077.
    Source Title
    The Computer Journal
    DOI
    10.1093/comjnl/bxw051
    ISSN
    0010-4620
    School
    Department of Computing
    URI
    http://hdl.handle.net/20.500.11937/54639
    Collection
    • Curtin Research Publications
    Abstract

    Agent-oriented technology is arguably one of the most substantial advances in software development. Several platforms and architectures have been developed to deal with its conception and the advantages that it entails. Of these architectures, the belief-desire-intention architecture is amongst the most prominent. This architecture utilizes a series of beliefs known to the agent in order to fulfil its desires given its intentions. Regardless of the agent platform or architecture, however, they all share the common trait of complexity. In sight of this, an increasing amount of research has been done in relation to model-driven approaches to their development. One such model-driven approach is the dynamic non-functional requirements-based approach. This approach utilizes a series of non-functional requirements to control the agents decision-making process, using the extended non-functional requirements framework as its underlying model. This paper presents the inclusion of a unique change management system through out this model-driven approach. This system is capable of categorizing changes, assigning them priorities based on various dynamics and determining their optimal incorporation time. To our knowledge, this is the first time that a change management model has been used in relation to model-driven agent creation. This approach is verified using a randomized empirical-based evaluation.

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