RUcore Resource Object
RUcore Resource Object
PDF-1(1.37 MB)
Uniform TitleA decision-theoretic control synthesis model for distributed systems
NameAmini, Ardavan (author), Jafari, Mohsen (chair), Boucher, Thomas (internal member), Altiok, Tayfur (internal member), Buczak, Anna (outside member), Mocanu, Stephane (outside member), Rutgers University, Graduate School-New Brunswick,
Degree Date2007
Date Created2007
SubjectIndustrial and Systems Engineering,
Distributed parameter systems,
Control theory,
Engineering systems
DescriptionThis dissertation presents a distributed control model built on a decision-theoretic framework, where intelligent beings (i.e., agents with their own controllers) are capable of utilizing their resources and functions to perform tasks in a dynamically and probabilistically changing environment. The intellectual merit of this work is to model the decision making process of agents in consideration of the non-determinism caused by: (i) probabilistic agent's behavior, i.e., probabilistic outcomes for agent's actions due to
failures, faults or other natural reasons; (ii) partially unknown and probabilistic environment, due to distributed nature of the system, lack of means for full observation within an agent or within the environment, lack of full knowledge about other agents' behaviors, and due to failures and faults occurring within the environment. The main novelty of this work comes from the way the decision making process of each agent, while modulated and distributed, constantly takes the benefit of what it learns from its environment and from itself. The decision making process of each agent includes
synthesizing task plans, and executing these plans.
failures, faults or other natural reasons; (ii) partially unknown and probabilistic environment, due to distributed nature of the system, lack of means for full observation within an agent or within the environment, lack of full knowledge about other agents' behaviors, and due to failures and faults occurring within the environment. The main novelty of this work comes from the way the decision making process of each agent, while modulated and distributed, constantly takes the benefit of what it learns from its environment and from itself. The decision making process of each agent includes
synthesizing task plans, and executing these plans.
Note[degree] Ph.D.
Note[bibliography] Includes bibliographical references (p. 181-186).
Genretheses
Persistent URLhttp://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.12830
LanguageEnglish
CollectionGraduate School - New Brunswick Electronic Theses and Dissertations
Organization NameRutgers, The State University of New Jersey
RightsThe author owns the copyright to this work.