Thesis (M. Phil.)--University of Hong Kong, 2006. / Title proper from title frame. Also available in printed format.

Thesis (M.S.)--University of Florida, 2005. / Title from title page of source document. Document formatted into pages; contains 61 pages. Includes vita. Includes bibliographical references.

Thesis (M.Phil.)--Hong Kong University of Science and Technology, 2006. / Includes bibliographical references (leaves 68-69). Also available in electronic version.

The theory of games seems to me to provide the most promising alternative to the traditional theories of social behaviour. Gaming modelS are inherently social in character (an individual's strategy choice in a game cannot even be properly defined without reference to at least one other individual) and they represent a radical departure from the "social stimulus - individual response" approach. They sean, furthermore, to be the only models which can adequately conceptualize an important (and large) class of social behaviours which arise from deliberate free choice. (From preface)

Automated devices enabled by wireless communications are deployed for a variety of purposes. As they become more ubiquitous, their interaction becomes increasingly important for coexistence when sharing a scarce resource, and for leveraging potential cooperation to achieve larger design goals. This thesis investigates the use of game theory as a tool for design and analysis of networked systems of automated devices in the areas of naval defence, wireless environmental monitoring through sensor networks, and cognitive radio wireless communications. In the first part, decentralized operation of naval platforms deploying electronic countermeasures against missile threats is studied. The problem is formulated as a stochastic game in which platforms independently plan and execute dynamic strategies to defeat threats in two situations: where coordination is impossible due to lack of communications, and where platforms hold different objectives but can coordinate, according to the military doctrine of Network Enabled Operations. The result is a flexible, robust model for missile deflection for advanced naval groups. Next, the problem of cooperative environmental monitoring and communication in energy-constrained wireless sensor networks is considered from a game-theoretic perspective. This leads to novel protocols in which sensors cooperatively trade off performance with energy consumption with low communication and complexity overhead. Two key results are an on-line adaptive learning algorithm for tracking the correlated equilibrium set of a slowly varying sensor deployment game, and an analysis of the equilibrium properties of threshold policies in a game with noisy, correlated measurements. Finally, the problem of dynamic spectrum access for systems of cognitive radios is considered. A game theoretic formulation leads to a scheme for competitive bandwidth allocation which respects radios' individual interests while enforcing fairness between users. An on-line adaptive learning scheme is again proposed for negotiating fair, equilibrium resource allocations, while dynamically adjusting to changing conditions. / Applied Science, Faculty of / Electrical and Computer Engineering, Department of / Graduate

The thesis considers the effects of public policy with respect to disclosure on rivalrous competition in duopolies. Principal contributions to the stochastic oligopoly theories of information sharing include imbedding an investment stage in the standard noncooperative two-stage information sharing/output (pricing) games under a wide range of assumptions about effects of investment or distributions of returns, and investigating the extent to which altering the usual preference assumption to allow risk aversion may affect information choice. At an information sharing level, it is established that, besides being sensitive to the type of competition and the nature of information asymmetries, as previously reported in the literature, private incentives to disclose also depend importantly on both the impact of investment and risk preferences. In this regard, equilibrium levels of investment are shown to be affected nontrivially by variance effects from investment, risk attitude of decision makers, as well as the type of industry rivalry. Also characterized are the welfare orderings obtained as a consequence of these varying disclosure effects on the decisions and hence profits of competing firms. If alternative accounting practices are distinguishable along the informativeness dimension, then, at an abstract level, the analysis can be seen as approaching the study of many accounting issues from a distinctly different perspective than the familiar tax or wealth transfer viewpoints. The principal contributions to the accounting literature include identifying the impact of disclosure rules or rule changes on industry, consumers, and society as a whole, and offering insights to the accounting policy makers concerning the results of disclosure regulation. / Business, Sauder School of / Graduate

This dissertation examines the role of negotiations in different institutional settings. In chapter one, I study how voluntary disclosure of information affects outcomes in plea bargaining. A prosecutor negotiates a sentence with a defendant who is privately informed about whether he is guilty or innocent. During negotiations, the prosecutor can investigate for evidence regarding the defendant’s type. If prosecutor and defendant do not reach an agreement, they go to trial and obtain payoffs that depend on the prosecutor’s evidence. Voluntary disclosure gives rise to endogenous second-order belief uncertainty. A purely sentence-motivated prosecutor might disclose exculpatory evidence. Voluntary disclosure leads to inefficient outcomes as parties might fail to reach an agreement. Mandatory disclosure is socially preferable: there is always agreement, and the defendant is better off if he is innocent and worse off if he is guilty. Furthermore, the prosecutor is better off under mandatory disclosure. In chapter two, I study how bargaining power affects bargaining outcomes between an entrepreneur and a venture capitalist who provides funds. Entrepreneur and venture capitalist openly disagree about noncontractible future decisions. The contract specifies control rights and cash-flow rights for each party. Noncontractible decisions are made by the party with control rights. When the entrepreneur has greater bargaining power and the investment value is large, she optimally relinquishes control rights. When the venture capitalist has more bargaining power, she always retains control rights. In general, greater disagreement makes the entrepreneur less likely to retain control rights. In chapter three, I study a bilateral bargaining model with endogenous recognition probabilities and endogenous surplus. At each period, players exert two types of costly effort: productive effort, which increases the surplus size, and unproductive effort, which affects the probability of being recognized as the proposer. I characterize how differences in the cost of exerting efforts affects outcomes. Advantages in unproductive effort affect the provision of both types of effort, but advantages in productive effort only affect the provision of that effort. Differences in time preferences only affect productive efforts when the probability of recognition is not persistent.

This thesis examines the corporate merger process as a bargaining game, under the assumption that the two companies are essentially in conflict over the single issue of the price to be offered by the acquirer to the target. The first part of the thesis deals with the construction and testing of analytical game-theoretic models to explain the proportion of the synergy gains accruing to the target company under different assumptions about the players' a priori knowledge. Assuming full certainty amongst the players about the pre- and post-merger values of the companies, the distribution of gains between target and acquiring companies that would be consistent with the Nash-Kalai axioms is determined in principle. The resulting model depends on the players' utility functions, and is parameterised by the relative bargaining strength of the players and their risk aversion coefficients. An operational version of the model is fitted to empirical data from a set of 24 recent mergers of companies quoted on the Johannesburg Stock Exchange. The model is shown to have good predictive power within this data set. Under the more realistic assumption of shared uncertainty amongst the two players about the post-merger value of the combined company, a Nash-Kalai bargaining model incorporating this uncertainty is developed. This model is an improvement over those with complete certainty in that it offers improved model fit in terms of predicting the total amount paid by an acquirer, and is able to dichotomise this payment into a cash amount and a share transfer amount. The theoretical model produced some results of practical value. Firstly, a cash-only offer is never optimal. Conditions under which shares only should be tendered are identified. Secondly, the optimal offer amount depends on the form of payment and the level of perceived risk. In a share-only offer the amount is constant regardless of risk, whilst if cash is included an increase in risk will imply a decrease in the optimal amount of cash offered. The Nash-Kalai model incorporating shared uncertainty is empirically tested on the same data set used previously. This allows a comparison with earlier results and estimation of the extent of the uncertainty. An extension of this model is proposed, incorporating an alternative form of the utility functions. The second part of the thesis makes use of ideas from negotiation analysis to construct a dynamic model of the complex processes involved in negotiation. It offers prescriptive advice to one of the players on likely Pareto-optimal bargaining strategies, given a description of the strategy the other party is likely to employ. The model describes the negotiating environment and each player's negotiating strategy in terms of a few simple parameters. The model is implemented via a Monte Carlo simulation procedure, which produces expected gains to each player and average transaction values for a wide range of each of the players' strategies. The resulting two-person game bimatrix is analysed to offer general insights into negotiated outcomes, and using conventional game-theoretic and Bayesian approaches to identify "optimal" strategies for each of the players. It is shown that for the purposes of identifying optimal negotiating strategies, the players strategies (described by parameters which are continuous in nature) can be adequately approximated by a sparse grid of discrete strategies, providing that these discrete strategies are chosen so as to achieve an even spread across the set of continuous strategies. A sensitivity analysis on the contextual parameters shows that the optimal strategy pair is very robust to changes to the negotiating environment, and any such changes that have the players start negotiating from positions more removed from one another is more detrimental to the target. A conceptual decision support system which uses the model and simulated results as key components is proposed and outlined.

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