We developed the Situation awareness-based Agent Transparency (SAT) model to support human operators’ situation awareness of the mission environment through teaming with intelligent agents. The model includes the agent's current actions and plans (Level 1), its reasoning process (Level 2), and its projection of future outcomes (Level 3). Human-inthe-loop simulation experiments have been conducted (Autonomous Squad Member and IMPACT) to illustrate the utility of the model for human-autonomy team interface designs. Across studies, the results consistently showed that human operators’ task performance improved as the agents became more transparent. They also perceived transparent agents as more trustworthy.
Jessie Y. C. Chen, Michael J. Barnes, Julia L. Wright, Kimberly Stowers, and Shan G. Lakhmani, "Situation awareness-based agent transparency for human-autonomy teaming effectiveness," Proc. SPIE 10194, Micro- and Nanotechnology Sensors, Systems, and Applications IX, 101941V (Presented at SPIE Defense + Security: April 12, 2017; Published: 18 May 2017); https://doi.org/10.1117/12.2263194.
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