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Optimizing Human-Autonomy Interaction: A Proposed Methodology

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Augmented Cognition (HCII 2025)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 15778))

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Abstract

Systems are currently available across a range of autonomy levels, though many may never be fully autonomous (i.e., Level 5, Society of Automotive Engineers International). Consequently, autonomous systems will require human supervisory control & resource management, further requiring designed artifacts for interaction. Connecting human operator input to discrete operations used by autonomous systems enables levels of automation that allow for cooperation and performance augmentation [23, 24] and can facilitate analyses to improve operator efficiency (e.g., [12]). Here, we introduce methods for characterizing complex, goal-driven behavior and determining critical paths that optimize interactions between human operators and artifacts for the supervisory control of autonomous systems. We propose applying cognitive task analyses (CTA) and task activity networks to discretize sequential behavior and conditional generative modeling [2, 15] to identify and evaluate critical paths to offer potential improvements to human-autonomy interactions.

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Acknowledgments

The opinions expressed herein are solely those of the authors and do not represent the official positions of the United States Government, the U.S. Department of Defense, the U.S. Air Force, or any of their subsidiaries or employees, or the United States Air Force. Distribution A. Approved for public release. Case number AFRL-2025-0295.

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Authors and Affiliations

  1. Air Force Research Laboratory, Wright-Patterson Air Force Base, OH, 45422, USA

    Christopher Myers & Taylor Curley

  2. BAE Systems, Inc., Space and Mission Systems, Dayton, OH, 45435, USA

    Margaret Ugolini

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  1. Christopher Myers
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  2. Margaret Ugolini
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Correspondence to Christopher Myers .

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  1. Soar Technology Inc., Orlando, FL, USA

    Dylan D. Schmorrow

  2. Katmai Government Services, Orlando, FL, USA

    Cali M. Fidopiastis

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The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as potential conflicts of interest. The reported study was approved by the Institutional Review Board at the Air Force Research Laboratory under protocol number FWR20240083H.

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Myers, C., Ugolini, M., Curley, T. (2025). Optimizing Human-Autonomy Interaction: A Proposed Methodology. In: Schmorrow, D.D., Fidopiastis, C.M. (eds) Augmented Cognition. HCII 2025. Lecture Notes in Computer Science(), vol 15778. Springer, Cham. https://doi.org/10.1007/978-3-031-93724-8_11

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  • DOI: https://doi.org/10.1007/978-3-031-93724-8_11

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