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Dissertation Final 31 May 2014.pdf (12.17 MB)

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Imperfect Situation Analysis: Representing the Role of Error and Uncertainty in Modeling, Simulation and Analysis

Middleton, Victor Eaton
http://rave.ohiolink.edu/etdc/view?acc_num=wright1401726956

Abstract Details

2014, Doctor of Philosophy (PhD), Wright State University, Engineering PhD.
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.
Frank Ciarallo, Ph.D. (Advisor)
Raymond Hill, Ph.D. (Committee Member)
Yan Liu, Ph.D. (Committee Member)
Mateen Rizki, Ph.D. (Committee Member)
Mary E. Fendley, Ph.D. (Committee Member)
David Hudak, Ph.D. (Committee Member)
305 p.
Armed Forces; Artificial Intelligence; Cognitive Psychology; Computer Science; Engineering; Industrial Engineering; Information Systems
Situation awareness; situation understanding; error; modeling; simulation; arc node networks; agent based modeling; intelligent agents, human-centric analysis; dismounted combatants; war games

Recommended Citations

Citations

  • Middleton, V. E. (2014). Imperfect Situation Analysis: Representing the Role of Error and Uncertainty in Modeling, Simulation and Analysis [Doctoral dissertation, Wright State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=wright1401726956

    APA Style (7th edition)

  • Middleton, Victor. Imperfect Situation Analysis: Representing the Role of Error and Uncertainty in Modeling, Simulation and Analysis . 2014. Wright State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=wright1401726956.

    MLA Style (8th edition)

  • Middleton, Victor. "Imperfect Situation Analysis: Representing the Role of Error and Uncertainty in Modeling, Simulation and Analysis ." Doctoral dissertation, Wright State University, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=wright1401726956

    Chicago Manual of Style (17th edition)

wright1401726956
1,100
© 2014, all rights reserved.
This open access ETD is published by Wright State University and OhioLINK.