The current air traffic concept of operations relies on a centralized process in which ground controllers are responsible for determining conflict-free trajectories. However, with new technologies such as ADS-B and GPS, aircraft could directly interact together to resolve their own conflicts in a decentralized manner. The challenge is to guarantee aircraft separation while converging to reasonably fair resolutions for all aircraft. The difficulty is that aircraft have only limited information about how the other aircraft evaluate the cost of conflict resolutions. Thus, this thesis proposes to frame decentralized conflict resolution using game theory. A collaborative decentralized conflict resolution is developed as a sequential bargaining process between the different aircraft. The goal of each aircraft is to minimize the cost associated with the conflict resolution. However, each aircraft doesn’t know the cost function and performance constraints of the other involved aircraft. In the sequential bargaining process developed, aircraft propose at each step personal trajectories to the other aircraft, corresponding to trajectories they would be ready to fly. Then they compute response trajectories, corresponding to trajectories they would have to fly to avoid the conflict if the personal trajectories were flown. If some response trajectories are cheaper than the offered personal trajectories, an agreement is reached; otherwise compromises have to be made by the aircraft by offering more expensive personal trajectories at the next step. Several pairwise conflict experiments, corresponding to different conflict geometries, were conducted to explore different ways of handling performance constraints and different ways of searching trajectories in the resolution space. Ultimately, the algorithm was demonstrated in a large scale simulation with more than a thousand aircraft flying over the Indianapolis Center, incurring more than five hundred conflicts. The traffic sets were taken from real ETMS data over five hours, to represent ‘real’ conditions. 93% of the conflicts were successfully solved by the bargaining process.

This work presents a computational tool that calculates optimally efficient safeguarding strategies at and across nuclear fuel cycle facilities for a cost-constrained inspector seeking to detect a state-facilitated diversion or misuse. The tool employs a novel methodology coupling a game theoretic solver with a probabilistic simulation model of a gas centrifuge enrichment plant and an aqueous reprocessing facility. The simulation model features a suite of defender options at both facilities, based on current IAEA practices, and an analogous menu of attacker proliferation pathway options. The simulation model informs the game theoretic solver by calculating the detection probability for a given inspector-proliferator strategy pair and weighting the detection probability by the quantity and quality of material obtained to generate a scenario payoff. Using a modified fictitious play algorithm, the game iteratively calls the simulation model until the equilibrium is reached and outputs the optimal inspection strategy, proliferation strategy, and the equilibrium scenario payoff. Two types of attackers are modeled: a breakout-willing attacker, whose behavior is driven by desire for high value material; and a risk-averse attacker, who desires high-value material but will not pursue a breakout strategy that leads to certain detection. Results are presented demonstrating the sensitivity of defender strategy to budget and attacker characteristics, for an attacker known to be targeting the enrichment or reprocessing facility alone, as well as an attacker who might target either facility. The model results indicate that the optimal defender resource allocation strategy across multiple facilities hardens both facilities equitably, such that both facilities are equally unattractive targets to the attacker. / text

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This dissertation uses cooperative and non-cooperative game theory to examine the role of investment (broadly defined) in social organization. It's composed of three chapters. The first chapter examines bidirectional investment in partnerships and characterizes the stable relationships among the benefits players produce and receive, their costs, and their payoffs. The second chapter extends the model of the first chapter to allow for multilateral matching and investment; it shows that many of the results of the bilateral case remain true in the more general case. The third chapter examines investment in social links to secure future help and characterizes the equilibrium network/linking architecture and welfare.

This thesis is an examination of the traveler’s dilemma and its backward induction argument. I begin by explaining relevant terminology, the prisoner’s dilemma, and the iterated prisoner’s dilemma; the discussion of which aids my examination of the traveler’s dilemma and its backward induction argument. My evaluation of the traveler’s dilemma involves a dissection of the game into its different components, a presentation of the salient similarities and differences between the traveler’s dilemma and the prisoner’s dilemma, and the exploration of three possible solutions. The first two solutions are adapted from ones initially created to solve other backward induction argument problems. The third solution is original and its foundation rests on the unique structure of the traveler’s dilemma. I focus on this third solution and consider several objections to it. I end this thesis with some ancillary comments about the possibility of generalizing the third solution to other backward induction argument problems.

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This thesis is an examination of the traveler’s dilemma and its backward induction argument. I begin by explaining relevant terminology, the prisoner’s dilemma, and the iterated prisoner’s dilemma; the discussion of which aids my examination of the traveler’s dilemma and its backward induction argument. My evaluation of the traveler’s dilemma involves a dissection of the game into its different components, a presentation of the salient similarities and differences between the traveler’s dilemma and the prisoner’s dilemma, and the exploration of three possible solutions. The first two solutions are adapted from ones initially created to solve other backward induction argument problems. The third solution is original and its foundation rests on the unique structure of the traveler’s dilemma. I focus on this third solution and consider several objections to it. I end this thesis with some ancillary comments about the possibility of generalizing the third solution to other backward induction argument problems.

Although project portfolio management (PPM) has been an active research area over the past 50 years, budget allocation models that consider competition are sparse. Firms faced with the project portfolio management problem must not only consider their current projections for the returns from their projects’ target markets, but must also anticipate that these returns can depend significantly on the investment decisions made by their competitors. In this thesis, we develop four Competitive PPM (CPPM) models wherein firms allocate resources between multiple projects and project returns are influenced by the actions taken by competitors. In the first two CPPM problems, we assume all-or-nothing project investment decisions where firms fully commit to either a project targeting a mature or an emerging market and the investment amount is fixed (first model) or a decision variable (second model). In the final two CPPM problems, firms have a fixed budget which they allocate in a continuous manner between two markets (third model) or multiple markets (fourth model). The returns each firm obtains from investments into these markets are assumed to follow an s-shaped curve (first model), the Inada (1963) conditions (third model), or are determined based on linear demand functions (second and fourth model). In the first model, two competing firms consider investing into two separate projects targeting a mature and an emerging market. We assume that firms have symmetric investment opportunities for each market and each firm simultaneously decides whether to invest in the mature or the emerging market. The returns from these markets are assumed to follow an s-shaped curve and depend on both firms’ investment decision. We characterize the variety of interactions that may emerge in symmetric environments (e.g., Prisoner’s Dilemma or Game of Chicken). For each game, we outline the CPPM strategy that can offer higher returns by exploiting first-mover advantages, cooperation opportunities and aggressive choices. We also discuss the market conditions that lead to these games. In the second model, a similar CPPM setting is considered where two symmetric firms face two target markets. However, we assume that demand for the emerging market is uncertain and may expand through firms’ market entry (positive diffusion effects), while demand for the mature market is known with certainty and cannot expand. Firms decide when to invest, in which market to invest, and how much to invest into this market. Our analysis reveals that the existence of multiple investment opportunities may induce firms to delay their investment even in the absence of demand uncertainty, and that high diffusion effects coupled with low demand uncertainty can drive firms to invest early even if both firms could increase returns by delaying their investment. We then study the asymmetric case where firms differ with respect to their costs and diffusion effects and show some counter-intuitive results. In the third CPPM problem, we consider continuous budget allocations and prove that while a monopoly firm bases its budget allocation decision solely on the marginal returns of the two markets, duopoly firms also account for their average returns from the two markets. This drives duopoly firms, in particular the firm with the smaller budget, to invest more heavily into the mature market. We show that as a firm’s budget increases, the share of its budget that is invested into the mature market decreases while its competitor’s investment into the mature market increases. This chapter also explores how changes to the market parameters and market uncertainty affect the resource allocation decision of firms under competition. Considering the special case of identical budgets, we prove that as the number of competing firms increases (with a fixed total budget), firms allocate an even greater share of their budget into the mature market. The fourth model considers a general case where a number of budget-constrained firms engage in production decisions for multiple markets under competition. Each firm decides how much to produce for each market, subject to its budget constraint. We prove that firms produce greater quantities for markets with higher than average base demand and that these quantities are increasing in the number of competitors (assuming identical production capacities). With asymmetric production capacities, we numerically illustrate how firms with large production capacities may, instead, increase production into lower than average base demand markets. Furthermore, we characterize the increase in return firms can expect from budget increases and conjecture that if some markets are not served by all firms, the remaining firms reduce their production into those markets where some firms are not producing.

iv, 215 leaves ; 26 cm. / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / Thesis (Ph.D.)--University of Adelaide, Dept. of Computing Science, 1974