depend on robustness properties of the solution concepts adopted. Chapter 1 discusses recent results in this research area … attention in the literature (namely, the distinction between knowledge and certainty), raising novel questions of robustness …

essential. The robustness of such inferences is dependent on sample size. The purpose of this study is to examine the impact of …

the policy that maximizes robustness to unstructured uncertainty. … uncertainty; that is, when uncertainty cannot be modeled with known probability distributions. Under these circumstances, the … and an aggregate abatement standard in terms of maximizing the range of uncertainty under which the welfare loss from …

robust. But robustness, in the sense of assurance against extreme outcomes, ordinarily is not the only desideratum in … the risk of a successful attack by inspecting more vessels, we show that robustness against the failure to guarantee a … minimum level of expected utility might not be monotonic. Robustness modeling based on expected utility and incorporating …

uncertainty due to lack of information, particularly for time-distant life cycle aspects. Under severe uncertainty, traditional … uncertainty formalisms require more information than is available. However, a recently devised formalism, information-gap decision … without needing more information or more complex uncertainty analysis.In this dissertation, IGDT is investigated and shown to …

uncertainty. A decision support framework was developed to allow the user to visualize the differences in performance and economic … for better traceability and bounding of uncertainty. Other findings regarding the use of a risk analysis early during …

uncertainty in the input parameters of a performance model. In one particular form of severely deficient information, a nominal …