Reasoning with imprecise trade-offs in decision making under certainty and uncertainty

In many real world situations, we make decisions in the presence of multiple, often conflicting and non-commensurate objectives. The process of optimizing systematically and simultaneously over a set of objective functions is known as multi-objective optimization. In multi-objective optimization, we have a (possibly exponentially large) set of decisions and each decision has a set of alternatives. Each alternative depends on the state of the world, and is evaluated with respect to a number of criteria. In this thesis, we consider the decision making problems in two scenarios. In the first scenario, the current state of the world, under which the decisions are to be made, is known in advance. In the second scenario, the current state of the world is unknown at the time of making decisions. For decision making under certainty, we consider the framework of multiobjective constraint optimization and focus on extending the algorithms to solve these models to the case where there are additional trade-offs. We focus especially on branch-and-bound algorithms that use a mini-buckets algorithm for generating the upper bound at each node of the search tree (in the context of maximizing values of objectives). Since the size of the guiding upper bound sets can become very large during the search, we introduce efficient methods for reducing these sets, yet still maintaining the upper bound property. We define a formalism for imprecise trade-offs, which allows the decision maker during the elicitation stage, to specify a preference for one multi-objective utility vector over another, and use such preferences to infer other preferences. The induced preference relation then is used to eliminate the dominated utility vectors during the computation. For testing the dominance between multi-objective utility vectors, we present three different approaches. The first is based on a linear programming approach, the second is by use of distance-based algorithm (which uses a measure of the distance between a point and a convex cone); the third approach makes use of a matrix multiplication, which results in much faster dominance checks with respect to the preference relation induced by the trade-offs. Furthermore, we show that our trade-offs approach, which is based on a preference inference technique, can also be given an alternative semantics based on the well known Multi-Attribute Utility Theory. Our comprehensive experimental results on common multi-objective constraint optimization benchmarks demonstrate that the proposed enhancements allow the algorithms to scale up to much larger problems than before. For decision making problems under uncertainty, we describe multi-objective influence diagrams, based on a set of p objectives, where utility values are vectors in Rp, and are typically only partially ordered. These can be solved by a variable elimination algorithm, leading to a set of maximal values of expected utility. If the Pareto ordering is used this set can often be prohibitively large. We consider approximate representations of the Pareto set based on ϵ-coverings, allowing much larger problems to be solved. In addition, we define a method for incorporating user trade-offs, which also greatly improves the efficiency.

“Something isn’t right here”: American exceptionalism and the creative nonfiction of the Vietnam War

In this thesis, I argue that few attempts were as effective in correcting the exceptionalist ethos of the United States than the creative nonfiction written by the veterans and journalists of the Vietnam War. Using critical works on creative nonfiction, I identify the characteristics of the genre that allowed Paul John Eakin to call it ‘a special kind of fiction.’ I summarise a brief history of creative nonfiction to demonstrate how it became a distinctly American form despite its Old World origins. I then claim that it was the genre most suited to the kind of ideological transformation that many hoped to instigate in U.S. society in the aftermath of Vietnam. Following this, the study explores how this “new” myth-making process occurred. I use Tim O’Brien’s If I Die in a Combat Zone and Philip Caputo’s A Rumor of War to illustrate how autobiography/memoir was able to demonstrate the detrimental effect that America’s exceptionalist ideology was having on its population. Utilising narrative and autobiographical theory, I contend that these accounts represented a collective voice which spoke for all Americans in the years after Vietnam. Using Neil Sheehan’s A Bright Shining Lie and C.D.B. Bryan’s Friendly Fire, I illustrate how literary journalism highlighted the hubris of the American government. I contend that while poiesis is an integral attribute of creative nonfiction, by the inclusion of extraneous bibliographic material, authors of the genre could also be seen as creating a literary context predisposing the reader towards an empirical interpretation of the events documented within. Finally, I claim that oral histories were in their essence a synthesis of “everyman” experiences very much in keeping with the American zeitgeist of the early Eighties. Focussing solely on Al Santoli’s Everything We Had, I demonstrate how such polyphonic narratives personalised the history of the Vietnam War.