Publication Date

2014

Document Type

Dissertation

Committee Members

Frank Ciarallo (Advisor), Mary E. Fendley (Committee Member), Raymond Hill (Committee Member), David Hudak (Committee Member), Yan Liu (Committee Member), Mateen Rizki (Committee Member)

Degree Name

Doctor of Philosophy (PhD)

Abstract

Much of traditional modeling, simulation and analysis (MS&A) is supported by engineering models - deterministic, Newtonian physics-based representations of closed systems. Such approaches are not well-suited to represent the intricacies of human behavior. This research advocates and seeks to articulate the concept of a more human- centric approach to MS& A, one that better represents decision-making and other cognitive aspects of human behavior as well as it does physical activity.

It starts with a view of individuals and groups as complex adaptive systems, which are best represented using agent-based modeling. Representation of human behavior through intelligent agents incorporates models of decision-making, knowledge engineering and knowledge representation, as well as the whole gamut of the psychological and physiological interactions of humans with each other and their environment. This representation is exemplified by consideration of situation awareness/situation understanding (SA/SU) as a core element. This leads to the development of a proof-of-concept simulation of a specific, easily understood, and quantifiable example of human behavior: intelligent agents being spatially "lost" while trying to navigate in a simulation world. This model is named MOdeling Being Intelligent and Lost (MOBIL), noting the ability to be in both of these states is central to the simulation. MOBIL uses a blend of object oriented software principles with agent based modeling to establish the utility of applying the human-centric approach to analysis.

Applying that simulation in a number of virtual experiments illustrates how it supports investigation into an individual's SA/SU and associated decision-making processes.

Page Count

305

Department or Program

Ph.D. in Engineering

Year Degree Awarded

2014


Included in

Engineering Commons

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