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The objective of this master thesis is to identify “key-drivers” embedded in customer satisfaction data. The data was collected by a large transportation sector corporation during five years and in four different countries. The questionnaire involved several different sections of questions and ranged from demographical information to satisfaction attributes with the vehicle, dealer and several problem areas. Various regression, correlation and cooperative game theory approaches were used to identify the key satisfiers and dissatisfiers. The theoretical and practical advantages of using the Shapley value, Canonical Correlation Analysis and Hierarchical Logistic Regression has been demonstrated and applied to market research.

In this thesis, we study different Internet pricing schemes and how they can be applied to a multiple ISP environment. We first take a look at the current Internet architecture. Then the different classes that make up the Internet hierarchy are discussed. We also take a look at peering among Internet Service Providers (ISPs) and when it is a good idea for an ISP to consider peering. Moreover, advantages and disadvantages of peering are discussed along with speculations of the evolution of the Internet peering ecosystem. We then consider different pricing schemes that have been proposed and study the factors that make up a good pricing plan. Finally, we apply some game theoretical concepts to discuss how different ISPs could interact together. We choose a pricing model based on a Stackelberg game that takes into consideration the effect of the traffic variation among different customers in a multiple ISP environment. It allows customers to specify their desired QoS in terms of maximum allowable end-to-end delay. Customers only pay for the portion of traffic that meet this delay bound. Moreover, we show the effectiveness of adopting this model through a comparison with a model that does not take traffic variation into account. We also develop a naïve case and compare it to our more sophisticated approach.

Bilateral incomplete-information negotiations of multiple issues present a difficult yet common negotiation problem that is complicated to solve from a mechanism design perspective. Unlike multilateral situations, where the individual aspirations of multiple agents can potentially be used against one another to achieve socially desirable outcomes, bilateral negotiations only involve two agents; this makes the negotiations appear to be a zero-sum game pitting agent against agent. While this is essentially true, the gain of one agent is the loss of the other, with multiple issues, it is not unusual that issues are valued asymmetrically such that agents can gain on issues important to them but suffer losses on issues of less importance. Being able to make trade-offs amongst the issues to take advantage of this asymmetry allows both agents to experience overall benefit. The major complication is negotiating under the uncertainty of incomplete information, where agents do not know each other's preferences and neither agent wants to be taken advantage of by revealing its private information to the other agent, or by being too generous in its negotiating. This leaves agents stumbling in the dark trying to find appropriate trade-offs amongst issues. In this work, we introduce the Bilateral Automated Mediation (BAM) framework. The BAM framework is aimed at helping agents alleviate the difficulties of negotiating under uncertainty by formulating a negotiation environment that is suitable for creating agreements that benefit both agents jointly. Our mediator is a composition of many different negotiation ideas and methods put together in a novel third-party framework that guides agents through the agreement space of the negotiation, but instead of arbitrating a final agreement, it allows the agents themselves to ratify the final agreement.

This thesis is divided into two parts. In Part I we introduce a new formalism for quantum strategies, which specify the actions of one party in any multi-party interaction involving the exchange of multiple quantum messages among the parties. This formalism associates with each strategy a single positive semidefinite operator acting only upon the tensor product of the input and output message spaces for the strategy. We establish three fundamental properties of this new representation for quantum strategies and we list several applications, including a quantum version of von Neumann's celebrated 1928 Min-Max Theorem for zero-sum games and an efficient algorithm for computing the value of such a game. In Part II we establish several properties of a class of quantum operations that can be implemented locally with shared quantum entanglement or classical randomness. In particular, we establish the existence of a ball of local operations with shared randomness lying within the space spanned by the no-signaling operations and centred at the completely noisy channel. The existence of this ball is employed to prove that the weak membership problem for local operations with shared entanglement is strongly NP-hard. We also provide characterizations of local operations in terms of linear functionals that are positive and "completely" positive on a certain cone of Hermitian operators, under a natural notion of complete positivity appropriate to that cone. We end the thesis with a discussion of the properties of no-signaling quantum operations.

This thesis considers the combination of Fuzzy logic and Kalman Filtering that have traditionally been considered to be radically different. The former is considered heuristic and the latter statistical. In this thesis a philosophical justification for their combination is presented. Kalman Filtering is revised to enable the incorporation of fuzzy logic in its formulation. This formulation is subsequently referred to as the Revised-Kalman Filter. Heuristic membership functions are then used in the Revised-Kalman Filter to substitute for the system and measurement covariance matrices to form a fuzzy rendition of the Kalman Filter. The Fuzzy Kalman Filter formulation is further revised according to a concept referred to as the Parallel Distributed Compensation to allow for further heuristic adjustment of the corrective gain. This formulation is referred to as the Parallel Distributed Compensated-Fuzzy Kalman Filter. <p> Simulated implementations of the above filters reveal that a tuned Kalman Filter provides the best performance. However, if conditions change, the Kalman filters performance degrades and a better performance is obtained from the two versions of the Fuzzy Kalman Filters.

Game balance is the problem of determining the fairness of actions or sets of actions in competitive, multiplayer games. This problem primarily arises in the context of designing board and video games. Traditionally, balance has been achieved through large amounts of play-testing and trial-and-error on the part of the designers. In this thesis, it is our intent to lay down the beginnings of a framework for a formal and analytical solution to this problem, combining techniques from game theory and machine learning. We first develop a set of game-theoretic definitions for different forms of balance, and then introduce the concept of a strategic abstraction. We show how machine classification techniques can be used to identify high-level player strategy in games, using the two principal methods of sequence alignment and Naive Bayes classification. Bioinformatics sequence alignment, when combined with a 3-nearest neighbor classification approach, can, with only 3 exemplars of each strategy, correctly identify the strategy used in 55\% of cases using all data, and 77\% of cases on data that experts indicated actually had a strategic class. Naive Bayes classification achieves similar results, with 65\% accuracy on all data and 75\% accuracy on data rated to have an actual class. We then show how these game theoretic and machine learning techniques can be combined to automatically build matrices that can be used to analyze game balance properties.

This study got its origin in the failed climate negotiations in the Copenhagen 2009 summit. By conducting a public good game, with participants from China and Sweden, my study indicates that previous studies on public good games can predict the outcome of the game to a quit large extent even though most of my statistical tests came out statistically insignificant. My study also indicates that by framing the game as climate negotiations there were no statistical significant difference on the level of contributions in comparison to the unframed versions of the game. The awareness of the issues with emissions, global warming and other environmental problems are pretty high but even so when push comes to shove gains in the short run are prioritized to gains in the long run. There are however hypothetical willingness to come to term with the environmental issues. The results of the study indicate that the outcome of the Copenhagen summit can be avoidable but would need additional experiments made on cultural differences and behavior.

<p>A majority of formal theoretic research in political science treats political parties as unitary actors, and endows them with decision-making powers not unlike those of strategic individuals. This is true both of most research in the spatial-theoretic tradition, as well as most game theoretic research in the field of comparative political-economy. In contrast, my dissertation examines strategic equilibria which arise when competition takes place simultaneously within parties over organizational control and between parties over political office. I first distinguish between three intra-organizational elements: a party's parliamentary group, its activist cadre, and its executive leaders. Chapters 2-4 develop a set of foundational game theoretic models which identify the equilibrium balance of power among these 3 organizational elements as a function of a country's electoral institutions and voters' relative responsiveness to marginal policy changes. In turn, this more complete understanding of intra-party competition sheds light on a number of important questions in comparative politics and comparative political-economy. For example, it helps to identify conditions under which Downsian vote-maximization is in fact a viable assumption in spatial theoretic models; conditions under which Duverger's argument that proportional representation (PR) should tend to generate multi-party competition may not apply; and, in contrast to Lijphart's famous argument, conditions under which PR may instigate rather than mediate social conflict. Ten months of intensive field research conducted in Turkey provide both the quantitative and the qualitative data which constitute the dissertation's most basic empirical material. This data includes primary and secondary source material on the history of intra-organizational competition in Turkey; observational and informant-based information on contemporary Turkish politics and the events of 2006-2008; and a data set of over 4,000 observations on party-switching in the Turkish Parliament (1987-2007).</p> / Dissertation

<p>The ability to digitize information goods such as music and movies and the growing accessibility of the Internet has led to online piracy and the emergence of a new class of retailers that specialize in digital downloads. Both online piracy and digital retailers have changed the dynamics of the information goods distribution channel. In my dissertation I focus on issues related to this change.</p><p>In the first chapter, "Digital music set free: the flip side of DRM," I study the effect of Digital Rights Management (DRM) mechanisms on the competition between traditional and digital retailers and on online piracy. DRM refers to technologies designed to control how end users may access, copy, or convert digital media. In the context of music downloads, DRM makes piracy of digital music more difficult, and until recently, most legal outlets for downloadable music only sold songs with DRM protection. Recently download retailers have convinced record companies to allow them to sell DRM-free music. The introduction of DRM-free music raises several important questions: Will music piracy increase as the opponents of DRM-free music predict? Will the music industry profits go up or down? How will CD retailers be affected? Will all labels start selling the unprotected (DRM-free) content? </p><p>I address these and related questions by developing a model of a music distribution channel that allows a record label to sell through both traditional CD retailers and iTunes-like download services at different wholesale prices. Among the interesting results, the analysis indicates that the level of piracy may decline when DRM protection is removed and that the traditional retailers much prefer to compete with distributors of pirated digital music rather than with legal music download services.</p><p>The competition between online and traditional retailers has led to interesting pricing policies on which I focus in the second chapter, "Digital movies at one simple price: the effect on competition." Online retailers tend to prefer uniform pricing (e.g. iTunes Store) where all "products" carry a single price, while traditional retailers do not have a policy of uniform prices. It is important to understand why one retailer should choose a single, uniform price and what impact it has on the competing retailer who chooses multiple prices. I focus specifically on the impact that single price policy adopted by digital retailer has on the traditional retailer. I also analyze the choice of uniform vs. differentiated pricing by modeling the competition between online and traditional retailers for vertically differentiated information goods. Importantly, I demonstrate how the asymmetric equilibrium we observe in the market today can change systematically with the nature of competition between the retailers.</p> / Dissertation