Date of Award
3-2016
Document Type
Thesis
Degree Name
Master of Science
Department
Department of Systems Engineering and Management
First Advisor
Michael E. Miller, PhD.
Abstract
Recent U.S. Air Force Research Laboratory strategy documents have suggested the need for research in human-agent teaming. Teaming supports a dynamic shift in roles between the human and the agent, depending upon human performance and mission needs. Further, because the performance of these agents will be highly dependent upon the state of the human and the mission, this strategy suggests the need for increased use of modeling to provide a broader understanding of the automated agent’s behavior. This thesis applies a combination of static modeling in SysML activity diagrams, dynamic modeling of human and agent behavior in IMPRINT, and human experimentation in a dynamic, event-driven environment. The dynamic models and human experiments are used to understand the effects of agent delay time on human behavior, performance, and workload, as well as team dynamics. The models and experiments illustrate that agent delay time has a significant effect upon team behavior, performance, and the roles assumed by the human and agent. Therefore, it is proposed that the consequences of agent timing are significant in the context of human agent teaming and that models, which incorporate the human and agent within a common modeling environment, can be useful in understanding this effect.
AFIT Designator
AFIT-ENV-MS-16-M-154
DTIC Accession Number
AD1054087
Recommended Citation
Goodman, Tyler J., "Understanding Effects of Autonomous Agent Timing on Human-Agent Teams Using Iterative Modeling, Simulation and Human-in-the-Loop Experimentation" (2016). Theses and Dissertations. 395.
https://scholar.afit.edu/etd/395