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In nature, society and technology many disordered systems exist, that show emergent behaviour, where the interactions of numerous microscopic agents result in macroscopic, systemic properties, that may not be present on the microscopic scale. Examples include phase transitions in magnetism and percolation, for example in porous unordered media, biological, and social systems. Also technological systems that are explicitly designed to function without central control instances, like their prime example the Internet, or virtual networks, like the World Wide Web, which is defined by the hyperlinks from one web page to another, exhibit emergent properties. The study of the common network characteristics found in previously seemingly unrelated fields of science and the urge to explain their emergence, form a scientific field in its own right, the science of complex networks. In this field, methodologies from physics, leading to simplification and generalization by abstraction, help to shift the focus from the implementation's details on the microscopic level to the macroscopic, coarse grained system level. By describing the macroscopic properties that emerge from microscopic interactions, statistical physics, in particular stochastic and computational methods, has proven to be a valuable tool in the investigation of such systems. The mathematical framework for the description of networks is graph theory, in hindsight founded by Euler in 1736 and an active area of research since then. In recent years, applied graph theory flourished through the advent of large scale data sets, made accessible by the use of computers. A paradigm for microscopic interactions among entities that locally optimize their behaviour to increase their own benefit is game theory, the mathematical framework of decision finding. With first applications in economics e.g. Neumann (1944), game theory is an approved field of mathematics. However, game theoretic behaviour is also found in natural systems, e.g. populations of the bacterium Escherichia coli, as described by Kerr (2002). In the present work, a combination of graph theory and game theory is used to model the interactions of selfish agents that form networks. Following brief introductions to graph theory and game theory, the present work approaches the interplay of local self-organizing rules with network properties and topology from three perspectives. To investigate the dynamics of topology reshaping, coupling of the so called iterated prisoners' dilemma (IPD) to the network structure is proposed and studied in Chapter 4. In dependence of a free parameter in the payoff matrix, the reorganization dynamics result in various emergent network structures. The resulting topologies exhibit an increase in performance, measured by a variance of closeness, of a factor 1.2 to 1.9, depending in the chosen free parameter. Presented in Chapter 5, the second approach puts the focus on a static network structure and studies the cooperativity of the system, measured by the fixation probability. Heterogeneous strategies to distribute incentives for cooperation among the players are proposed. These strategies allow to enhance the cooperative behaviour, while requiring fewer total investments. Putting the emphasis on communication networks in Chapters 6 and 7, the third approach investigates the use of routing metrics to increase the performance of data packet transport networks. Algorithms for the iterative determination of such metrics are demonstrated and investigated. The most successful of these algorithms, the hybrid metric, is able to increase the throughput capacity of a network by a factor of 7. During the investigation of the iterative weight assignments a simple, static weight assignment, the so called logKiKj metric, is found. In contrast to the algorithmic metrics, it results in vanishing computational costs, yet it is able to increase the performance by a factor of 5.
Die Quantenspieltheorie stellt eine mathematische und konzeptuelle Erweiterung der klassischen Spieltheorie dar. Der Raum aller denkbaren Entscheidungswege der Spieler wird vom rein reellen, messbaren Raum in den Raum der komplexen Zahlen (reelle und imaginäre Zahlen) ausgedehnt. Durch das Konzept der möglichen quantentheoretischen Verschränkung der Entscheidungswege im imaginären Raum aller denkbaren Quantenstrategien können gemeinsame, durch kulturelle oder moralische Normen entstandene Denkrichtungen mit einbezogen werden. Ist die Strategienverschränkung der Spieler im imaginären Raum der denkbaren Entscheidungswege nur genügend groß, so können zusätzliche Nash-Gleichgewichte auftreten und zuvor existente dominante Strategien sich auflösen. Die der evolutionären Entwicklung zugrundeliegende Replikatordynamik besitzt in der evolutionären Quantenspieltheorie eine komplexere Struktur und die jeweiligen evolutionär stabilen Strategien können sich, abhängig vom Maß der Verschränkung, abändern. Neben einer detaillierten Darstellung der evolutionären Quantenspieltheorie werden in dieser Dissertation mehrere Anwendungsbeispiele besprochen. So wird durch eine quantentheoretische Erweiterung die aktuelle Finanzkrise mittels eines Anti-Koordinationsspiels beleuchtet, das unterschiedliche Publikationsverhalten von Wissenschaftlern erklärt und erste Ansätze einer experimentellen Bestätigung der Theorie dargestellt.