Incentive Control Strategies for Decision Problems With Parametric Uncertainties (Large Scale Systems, Game Theory, Stochastic, Coordination, Sensitivity Analysis)
Cansever, Derya H.
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https://hdl.handle.net/2142/69312
Description
Title
Incentive Control Strategies for Decision Problems With Parametric Uncertainties (Large Scale Systems, Game Theory, Stochastic, Coordination, Sensitivity Analysis)
Author(s)
Cansever, Derya H.
Issue Date
1985
Department of Study
Electrical Engineering
Discipline
Electrical Engineering
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Physics, Electricity and Magnetism
Abstract
The central theme of this thesis is the design of incentive control policies in large scale systems with hierarchical decision structures, under the stipulation that the objective functionals of the agents at the lower level of the hierarchy are uncertain to the top-level controller (the leader). These uncertainties are modeled as a finite-dimensional parameter vector whose exact value constitutes private information to the relevant agent at the lower level. The approach we have adopted is to design incentive policies for the leader such that the dependence of the decision of the agents on the uncertain parameter is minimized. We have identified several classes of problems for which this approach is feasible. In particular, we have constructed policies whose performance is arbitrarily close to the solution of a version of the same problem that does not involve uncertainties. We have also shown that for a certain class of problem wherein the leader observes a linear combination of the agents' decisions, the leader can achieve the performance he would obtain if he had observed each decision separately.
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