This research aims to dispel the myth that export cartels should be prohibited because they restrain competition and, thus, holds back economic development. It also proposes the conditions under which export cartels promote economic development. In contrast to the myth, this research argues that, when it comes to economic development, competition is not always desirable and, therefore, that export cartels should be formed under certain conditions. In other words, the doctrine that maximum competition is optimal competition is not applicable when the objective is economic development. Moreover, as export cartels from developing countries do not possess market power in the global market, if they facilitate their firms, which are mainly SMEs, to be able to export, competition in the global market is increased, rather than decreased. We then propose the concept of competition relocation, which argues that cartelisation does not eliminate competition but relocate competition from the activity being cartelised into other activities. The concept rejects the conventional interpretation of competition as a unidimensional action, in which cartels always decrease competition. On the contrary, competition is multidimensional, i.e., firms compete across different activities. Therefore, cartelisation may not eliminate or decrease competition but simply relocates it across different activities and the overall degree of competition might even increase. Export cartels is simply a tool to relocate competition. Based on the concept of competition relocation, we argue further that, in order to promote economic development, we must make sure that whenever cartelisation promotes the long-term productive capabilities more than competition does, cartelisation should be promoted. To derive the conditions under which export cartels should be promoted, we used both history and game theory. We study the historical lessons of now-developed countries, including Germany, the US, and Japan and draw a game-theoretical model to derive the conditions under which export cartels promote economic development. In terms of game theory, we propose that the situation in which export cartels should be promoted resembles the stag-hunt game, where both cartelisation and competition are Nash equilibria. Even though it is more productive to hunt a stag together, each hunter has an incentive to deviate and catch a hare. The model shows that, whenever the benefit of sharing resources between firms is sufficiently large (in comparison with other parameters), export cartels are more productive than competition. Therefore, most export cartels have been promoted among SMEs. Moreover, it also shows that, even though each firm may be able to export (due to abundant exclusive resources), the environment, which supports the use of resources across firms, could still make export cartels more productive.

Kommunikation entsteht, ohne dass hierfür notwendigerweise semantische oder syntaktische Regeln definiert werden müssen: Irgendwann haben unsere Vorfahren erlernt, miteinander zu kommunizieren, ohne dass ihnen jemand erklärte, wie das geht. In dieser Arbeit wird der philosophischen Frage nachgegangen, wie das möglich ist. Es soll geklärt werden, welche Bedingungen im Abstrakten dafür hinreichend sind, dass Wesen miteinander zu kommunizieren erlernen, und zwar insbesondere, ohne dass man ihnen hierfür eine konkrete Sprache vorgibt. Die Arbeit baut auf neuen Modellen und Erkenntnissen aus der Signalspieltheorie auf. Diese belegen, dass selbst einfache verstärkungsbasierte Lernverfahren in bestimmten Koordinierungsproblemen selbständig erlernen können, Information miteinander auszutauschen. Diese Erkenntnisse werden in dieser Arbeit mit Techniken aus dem maschinellen Lernen, insbesondere aus dem Bereich des deep reinforcement learning, kombiniert. Hiermit soll demonstriert werden, dass rudimentär intelligente Akteure selbstständig in relativ komplexen Sprachen miteinander kommunizieren können, wenn dies einer effizienteren Lösung nicht-trivialer Koordinierungsprobleme dient. Anders als in vergleichbaren Ansätzen, werden die lernfähigen Algorithmen, die in dieser Arbeit zum Einsatz kommen, weder dazu trainiert, real existierende Sprachen zu benutzen, noch werden sie dazu programmiert, künstliche Protokollsprachen zu verwenden. Vielmehr wird ihnen lediglich eine Menge von Signalen vorgegeben. Sowohl die syntaktischen Regeln, wie diese Signale aneinandergereiht werden dürfen, als auch die Semantik der Signale entstehen von alleine. / Communication emerges without the need for explicit definitions of semantic or syntactic rules: At some point, our ancestors learned to communicate with one another without anyone explaining to them how to do that. In this work, I'll try to answer the philosophical question of how that is possible. The goal is to find abstract conditions that are sufficient for the emergence of communication between creatures that do not have any predefined language available to them. This work builds on recent models and insights from the theory of signaling games. There, it is shown that simple reinforcement learning agents are able to learn to exchange meaningful information in suitable coordination problems autonomously. These insights will be combined with more powerful deep reinforcement learning techniques. Thus, it shall be demonstrated that moderately intelligent agents can learn to communicate in relatively complex languages, if this is useful to them in sufficiently non-trivial coordination problems. In contrast to existing work on communication based on artificial intelligence, the learning algorithms that will be applied here, will neither be trained to communicate in an existing natural language, nor will they be hard coded to use a predefined protocol. Instead, they will construct their messages freely from arbitrary sets of signals. The syntactic rules according to which these elementary signals can be chained together, as well as their semantics, will emerge autonomously.