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A Pragmatic Cognitive System Engineering Approach to Model Dynamic Human Decision-Making Activities in Intelligent and Automated Systems

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Conference paper

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Defence Research and Development Canada, Valcartier, has undertaken Research and Development RD work to provide Canadian warships with a revolutionary decision support capability explicitly designed to make the automation transparent and provide warfighters with effective and trusted decision support. This effort uses cognitive system engineering CSE as the essential design framework. CSE approaches are well suited to deal with decision support issues, but in practice are very expensive to conduct, time consuming, and inefficient from a design process perspective. With the latter limitations in mind, a pragmatic CSE approach, known as Applied Cognitive Work Analysis ACWA, was developed to bridge - in a structured, efficient, and converging way - the gap between cognitive analysis and design. As a result, the cost to conduct CSE analyses using the ACWA approach is reduced and analysis-design efficiency is significantly improved. This makes it easier to identify decision-aiding concepts suited to provide effective decision support. This paper presents a brief overview of CSE analysis methods and their benefits, particularly ACWA. It also presents some lessons learned when using ACWA for a specific project. Specifically, the first three steps of the ACWA approach were used during the initial phase of the ATAC Advanced Threat Assessment Capability project for the Canadian Navy. One important requirement for that project was to use a formal modeling and design approach that allowed one to trace back the origin of a specific algorithm development. The ACWA approach in concert with a systematic documentation methodology FAH and its artifacts was found to be very useful in the ATAC project, as it provided the means to meet that traceability requirement. 2 tables, 17 refs.

Subject Categories:

  • Administration and Management
  • Cybernetics
  • Naval Surface Warfare
  • Human Factors Engineering and Man Machine Systems
  • Command, Control and Communications Systems

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