Graduate Thesis Or Dissertation

Achieving Transparency in Human-Collective Systems

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  • Collective robotic systems are biologically-inspired and exhibit behaviors found in spatial swarms (e.g., fish), colonies (e.g., ants), or a combination of both (e.g., bees). Collective robotic system popularity continues to increase due to their apparent global intelligence and emergent behaviors. Many applications can benefit from the incorporation of collectives, including environmental monitoring, disaster response missions, and infrastructure support. Human-collective system designers continue to debate how best to achieve transparency in human-collective systems in order to attain meaningful and insightful information exchanges between the operator and collective, enable positive operator influence on collectives, and improve the human-collective's performance. Few human-collective evaluations have been conducted, many of which have only assessed how embedding transparency into one system design element (e.g., models, visualizations, or control mechanisms) may impact human-collective behaviors, such as the human-collective performance. This dissertation developed a transparency definition for collective systems that was leveraged to assess how to achieve transparency in a single human-collective system. Multiple models and visualizations were evaluated for a sequential best-of-\textit{n} decision-making task with four collectives. Transparency was evaluated with respect to how the model and visualization impacted human operators who possess different capabilities, operator comprehension, system usability, and human-collective performance. Transparency design guidance was created in order to aid the design of future human-collective systems. One set of guidelines were inspired from the results and discussions of the single human-collective analyses and another set were based on a review of the biological literature. This dissertation can be used to aid designers achieve transparency in human-collective systems. The primary contributions are: 1. A transparency definition for human-collective systems that describes the process of identifying what factors affect and are influenced by transparency, why those factors are important, and how to design a system to achieve transparency. 2. An expansive set of metrics that successfully evaluated how transparency influenced operators with different individual capabilities, operator comprehension, system usability, and human-collective performance. 3. The recommendation that system transparency quantification requires evaluating the transparency embedded into the various system design elements in order to determine how they interact with one another and influence the human-collective interactions and performance. 4. Design guidance recommendations with respect to models, visualizations, and control mechanisms in order to inform designers how transparency can be achieved for human-collective systems.
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  • US Office of Naval Research Awards N000141613025 and N000141812831



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