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  <title><![CDATA[MS Proposal by David Grimm]]></title>
  <body><![CDATA[<p><strong>Name:</strong>&nbsp;<strong>David Grimm</strong></p>

<p><strong>Master&rsquo;s Thesis Proposal Meeting</strong><br />
<strong>Date:</strong>&nbsp;November 22, 2019<br />
<strong>Time:</strong>&nbsp;1:00 pm<br />
<strong>Location:&nbsp;</strong>J.S. Coon Building, Room 148<br />
&nbsp;<br />
<strong>Advisor:</strong><br />
Jamie Gorman, Ph.D. (Georgia Tech)<br />
&nbsp;<br />
<strong>Thesis Committee Members:</strong></p>

<p>Jamie Gorman, Ph.D. (Georgia Tech)<br />
Richard Catrambone, Ph.D. (Georgia Tech)</p>

<p>Rick Thomas, Ph.D. (Georgia Tech)</p>

<p>Nancy Cooke, Ph.D. (Arizona State)<br />
&nbsp;<br />
<strong>Title:&nbsp;Dynamical Analysis and Modeling of Team Resilience in Human-Autonomy Teams</strong></p>

<p>&nbsp;</p>

<p><strong>Abstract:</strong></p>

<p>A resilient team would be good at overcoming sudden, difficult changes. A more resilient team would be faster at overcoming unanticipated challenges. In this study, I propose to analyze data from three-person teams to analyze resilience in human-autonomy teams operating in a remotely piloted aircraft system (RPAS) under a variety of instilled failures. To this end, I will analyze data collected across two experiments examining human autonomy team performance in a Wizard of Oz setting. I will analyze different layers of sociotechnical elements of the system, using entropy to represent system reorganization. Team performance will be measured by the successful completion of simulated reconnaissance missions, a coordination-based target processing efficiency (TPE) score to quantify team efficiency and effectiveness, and a ground truth resilience score used to identify how teams perform following an instilled failure. I will analyze system reorganization behavior using the root mean squared error (RMSE) metric across all system layers using a nonlinear prediction algorithm to quantify adaptive behavior. To measure resilience, I will utilize the RMSE measure in addition to layered entropy values and examine the time taken to achieve extreme values of reorganization during the duration of an instilled failure. In this way, I hope that these findings extend to the training of human-autonomy teams within a RPAS environment.</p>

<p>&nbsp;</p>
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