Group Title: Simulation-baed approach for decision making and route planning
Title: Simulation-based approach for decision making and route planning
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 Material Information
Title: Simulation-based approach for decision making and route planning
Physical Description: vii, 134 leaves : ill. ; 29 cm.
Language: English
Creator: Lee, Jin Joo ( Dissertant )
Fishwick, Paul A. ( Thesis advisor )
Bai, Sherman X. ( Reviewer )
Dankel, Douglas D. ( Reviewer )
Davis, Timothy D. ( Reviewer )
Fu, Li-Min ( Reviewer )
Publisher: Department of Computer and Information Science and Engineering, University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 1996
Copyright Date: 1996
Subjects / Keywords: Computer and Information Science and Engineering thesis, Ph. D.
Dissertations, Academic -- UF -- Computer and Information Science and Engineering
Genre: bibliography   ( marcgt )
theses   ( marcgt )
Abstract: Decision making is an active area of research in simulation, systems engineering and artifcial intelligence. One subset area of decision making, automated route planning, is covered in this work with our approach based on the technique of simulation rather than on purely heuristic or geometric techniques. This new technique is called simulation- based planning (SBP). Simulation-based planning is useful for route planning under various conditions including uncertain locations and events with potential adversarial activity. We propose that it is only by using simulation that one can make the most effective plan in uncertain and complex environments. SBP extends the planning area mainly in three aspects. First probabilistic uncertainty is handled through detailed and replicated simulation of models rather than solving them analytically, for example, using probability theory. Second, simulation models naturally extend the level of reasoning to greater detail, often involving continuous state space_ Thus, SBP is able to produce plans that are closer to the level of execution. Additionally, one can often discover subtleties that may be missed by higher level planners which are often rule-based. Third, the complexity of multiagent adversarial planning breaks down when object-oriented multimodel simulation is used. Here, each agent or adversary is individually modeled and simulated in response to each plan. In addition, to ensure that SBP can be used within reasonable time constraints, we develop general experimental design algorithms and techniques which reduce the overall simulation time.
General Note: Typescript.
General Note: Vita
Thesis: Thesis (Ph. D.)--University of Florida, 1996.
Bibliography: Includes bibliographical references (leaves 131-133).
 Record Information
Bibliographic ID: UF00101368
Volume ID: VID00001
Source Institution: University of Florida
Holding Location: University of Florida
Rights Management: All rights reserved by the source institution and holding location.
Resource Identifier: alephbibnum - 002117985


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