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Hum.-Robot Interact."],"published-print":{"date-parts":[[2022,9,30]]},"abstract":"<jats:p>As development of robots with the ability to self-assess their proficiency for accomplishing tasks continues to grow, metrics are needed to evaluate the characteristics and performance of these robot systems and their interactions with humans. This proficiency-based human-robot interaction (HRI) use case can occur before, during, or after the performance of a task. This article presents a set of metrics for this use case, driven by a four-stage cyclical interaction flow: (1)\u00a0robot self-assessment of proficiency (RSA), (2)\u00a0robot communication of proficiency to the human (RCP), (3)\u00a0human understanding of proficiency (HUP), and (4)\u00a0robot perception of the human\u2019s intentions, values, and assessments (RPH). This effort leverages work from related fields including explainability, transparency, and introspection, by repurposing metrics under the context of proficiency self-assessment. Considerations for temporal level (a priori, in situ, and post hoc) on the metrics are reviewed, as are the connections between metrics within or across stages in the proficiency-based interaction flow. 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