  The North Carolina Agriculture and Technical State University (NC A&T) in
collaboration with Georgia Tech Research Institute (GTRI) has developed
methodologies for creating simulation-based technology tools that are capable
of inferring the perceptions and behavioral states of autonomous systems. These
methodologies have the potential to provide the Test and Evaluation (T&E)
community at the Department of Defense (DoD) with a greater insight into the
internal processes of these systems. The methodologies use only external
observations and do not require complete knowledge of the internal processing
of and/or any modifications to the system under test. This paper presents an
example of one such simulation-based technology tool, named as the Data-Driven
Intelligent Prediction Tool (DIPT). DIPT was developed for testing a
multi-platform Unmanned Aerial Vehicle (UAV) system capable of conducting
collaborative search missions. DIPT's Graphical User Interface (GUI) enables
the testers to view the aircraft's current operating state, predicts its
current target-detection status, and provides reasoning for exhibiting a
particular behavior along with an explanation of assigning a particular task to
it.
