Thesis (M.S.)--Georgia State University, 2007. / Title from file title page. Xiaolin Hu, committee chair; Rajshekhar Sunderraman, Ying Zhu, committee members. Electronic text (71 p. : ill. (some col.)) : digital, PDF file. Description based on contents viewed Jan. 29, 2008. Includes bibliographical references (p. 70-71).

Thesis--Ph. D., University of Hong Kong. / Contents: v.1. Text.- v.2. Appendices. Typewritten.

The Department of Defense has always had an interest in simulation systems for training and analysis. Recently, simulation usage in training has been stressed. Simulation systems provide an easy and effective way for trainees to learn military doctrine and small unit tactics. In order to be effective, a simulation must accurately represent the real world. Sensory perception is one important real world influence that should be modeled. Modular Semi-Automated Forces (ModSAF) is a highly advanced computer simulation system that can model the movement, formations, equipment and other aspects of armed forces with precise calculations. In spite of all of the advances in ModSAF and other systems like it, the behaviors of sound and how they affect the warfighter have been scarcely modeled. The goal of this project is to investigate how sound is produced, propagated, and detected (acoustics), the behavioral effects sound has on the human psyche, and model the findings. It includes the development of a computer model of the physical phenomenon relating to sound, to be incorporated within ModSAF or another similar constructive simulation system.

Literature on the modeling and simulation of complex adaptive systems (cas) has primarily advanced vertically in different scientific domains with scientists developing a variety of domain-specific approaches and applications. However, while cas researchers are inherently interested in an interdisciplinary comparison of models, to the best of our knowledge, there is currently no single unified framework for facilitating the development, comparison, communication and validation of models across different scientific domains. In this thesis, we propose first steps towards such a unified framework using a combination of agent-based and complex network-based modeling approaches and guidelines formulated in the form of a set of four levels of usage, which allow multidisciplinary researchers to adopt a suitable framework level on the basis of available data types, their research study objectives and expected outcomes, thus allowing them to better plan and conduct their respective research case studies. Firstly, the complex network modeling level of the proposed framework entails the development of appropriate complex network models for the case where interaction data of cas components is available, with the aim of detecting emergent patterns in the cas under study. The exploratory agent-based modeling level of the proposed framework allows for the development of proof-of-concept models for the cas system, primarily for purposes of exploring feasibility of further research. Descriptive agent-based modeling level of the proposed framework allows for the use of a formal step-by-step approach for developing agent-based models coupled with a quantitative complex network and pseudocode-based specification of the model, which will, in turn, facilitate interdisciplinary cas model comparison and knowledge transfer. Finally, the validated agent-based modeling level of the proposed framework is concerned with the building of in-simulation verification and validation of agent-based models using a proposed Virtual Overlay Multiagent System approach for use in a systematic team-oriented approach to developing models. The proposed framework is evaluated and validated using seven detailed case study examples selected from various scientific domains including ecology, social sciences and a range of complex adaptive communication networks. The successful case studies demonstrate the potential of the framework in appealing to multidisciplinary researchers as a methodological approach to the modeling and simulation of cas by facilitating effective communication and knowledge transfer across scientific disciplines without the requirement of extensive learning curves.

Thesis (MSc (Computer science))--University of Pretoria, 2008. / Includes bibliographical references (p. 143-147)

Thesis (M.S. in Modeling, Virtual Environments and Simulation (MOVES))--Naval Postgraduate School, Sept. 2004. / Thesis Advisor(s): Christian J. Darken. Includes bibliographical references (p. 93-95). Also available online.

Thesis (M.S. in Information Technology Management and M.S. in Computer Science)--Naval Postgraduate School, March 2005. / Thesis Advisor(s): Alexander Bordetsky, Gilbert M. Lundy. Includes bibliographical references (p. 69-75). Also available online.