<> "The repository administrator has not yet configured an RDF license."^^ . <> . . "Strategic Interaction under Uncertainty"^^ . "The theory of strategic interaction or, game theory, for short, plays an important role in\r\neconomics. It can offer insights into situations in which two or more interacting individuals\r\nchoose actions that jointly affect the payoff of each party. Game-theoretic applications\r\ncover a wide range of economic, political and social situations such as auctions, contract\r\nformation, bargaining situations, political competition, and public good provision, to\r\nonly name a few. This broad scope of application makes it a powerful concept. Most\r\ngames involve some kind of uncertainty. For instance, players may be uncertain about\r\nthe strategy choice of other players or they may lack information about the strategic\r\nenvironment.\r\nGame theory is closely tied to decision theory. In fact, the former can be viewed as\r\nthe natural extension of the latter. In the words of Myerson (1991, p. 5): \"The logical\r\nroots of game theory are in Bayesian decision theory. Indeed, game theory can be viewed\r\nas an extension of decision theory [...]. Thus, to understand the fundamental ideas of\r\ngame theory, one should begin by studying decision theory.\" Bayesian decision theory\r\nassumes that decision makers' subjective beliefs can be represented by unique probability\r\nmeasures and that they update their prior beliefs in accordance with Bayes' rule when\r\nreceiving new information. Furthermore, Bayesian decision-makers usually are subjective\r\nexpected utility maximizers. Savage (1954) provided an axiomatic foundation for the\r\nBayesian approach. His subjective expected utility theory has become the leading model\r\nof choice under uncertainty.\r\n\r\nHowever, Ellsberg (1961) questioned the descriptive adequacy of subjective expected\r\nutility theory. He exempliffed that the choice behavior of many subjects is not consistent\r\nwith Savage's theory when facing \"ambiguous uncertainty\", or \"ambiguity\", that is, a\r\nsituation in which some events have known probabilities, whereas for other ones the\r\nprobabilities are unknown. Ellsberg's observation has received powerful empirical support\r\nin the last decades (see Camerer and Weber, 1992). In this thesis, the term \"uncertainty\"\r\nwill be used as a generic term to cover both ambiguity and non-ambiguous uncertainty\r\n(\"risk\"). To represent behavior as observed by Ellsberg, several alternatives to subjective\r\nexpected utility theory have been suggested in recent years. Two prominent alternatives\r\nare Choquet expected utility theory of Schmeidler (1989) and the multiple prior approach\r\nof Gilboa and Schmeidler (1989). More recent examples are the smooth ambiguity model\r\nof Klibanoff et al. (2005) and the variational model of Maccheroni et al. (2006).\r\nThe main goal of this thesis is to shed some light on the impact of ambiguity-sensitive\r\nbehavior on strategic decision-making in interactive situations. As Crawford (1990, p.\r\n152) appropriately expressed it: \"In recent years, non-expected utility decision models\r\nhave given us significantly better explanations of observed behavior in nonstrategic environments.\r\nThese successes, and the weight of the experimental evidence against the\r\nexpected utility hypothesis, suggest that much might be learned about strategic behavior\r\nby basing applications of game theory on more general models of individual decisions\r\nunder uncertainty.\" In this spirit, the present thesis investigates non-cooperative game\r\nmodels that are based on alternative models of individual decision-making under uncertainty.\r\nThe main body of this dissertation consists of three chapters (Chapters 4, 5 and\r\n6), each of which studies strategic interaction under uncertainty. Chapter 4 and 5 explore\r\nformal models in which uncertainty arises from exogenous chance moves and incomplete\r\ninformation, respectively. While the game studied in Chapter 4 does not involve private\r\ninformation, the model in Chapter 5 allows for private information. Chapter 6 experimentally\r\nexamines the extent to which a lack of information about others' preferences\r\naffects subject behavior. It is shown that a strategic ambiguity model as well as a quasi\r\nBayesian model of incomplete information explain the findings better than standard Nash equilibrium. \r\n\r\nThe results of chapters 4 and 6 are based on collaborative work with Boris Wiesenfarth (Chapter 4), and Christoph Brunner and Hannes Rau (Chapter 6).\r\nThis thesis is organized as follows. Chapter 2 outlines the decision-theoretic foundations\r\nof the interactive models studied in this work. First, the historical development of\r\nmodern decision theory is briefly reviewed. I recall in some detail the fundamentals of\r\nsubjective expected utility theory as well as the experiments by Ellsberg (1961). Finally,\r\nalternative models of choice under uncertainty are considered, especially, the Choquet\r\nexpected utility model and the multiple prior model. These models will be used in subsequent\r\nchapters. Chapter 3 discusses some conceptual foundations of non-cooperative\r\ngame theory. It starts with sketching the historical roots of modern game theory. Basic\r\nconcepts such as the concept of a game and the Nash equilibrium concept are recalled.\r\nThe last part of this chapter deals with different sources of uncertainty in games. In the\r\ncontext of strategic uncertainty, I describe generalized equilibrium concepts that allow for\r\nplayers whose preferences are not represented by expected utility functionals. Furthermore,\r\nI review the class of Bayesian games introduced by Harsanyi (1967-68) to analyze\r\ngames of incomplete information.\r\nIn Chapter 4, a Hotelling duopoly game that incorporates ambiguous uncertainty\r\nabout the market demand is examined. The key assumption of this model is that firms'\r\nbeliefs are represented by neo-additive capacities introduced by Chateauneuf et al. (2007).\r\nThe related literature is reviewed and the model is specified. Moreover, this chapter discusses\r\nimplications for possible applications of the Capacity model and limitations of\r\nthe existing models. Chapter 5 investigates the extent to which we can distinguish expected\r\nand uncertainty-averse non-expected utility players on the basis of their behavior.\r\nA model of incomplete information games is used in which players can choose mixed\r\nstrategies. First, this model is illustrated by two examples and described in detail. The\r\nfollowing part of the chapter provides the results. Subsequently, I discuss the underlying\r\nmodel and introduce a generalized equilibrium concept. Chapter 6 reports on the results\r\nof the aforementioned experimental study testing whether revealing players' preferences to\r\neach other leads to more equilibrium play. Chapter 7 concludes with an overall summary."^^ . "2016" . . . . . . . "Till Florian"^^ . "Kauffeldt"^^ . "Till Florian Kauffeldt"^^ . . . . . . "Strategic Interaction under Uncertainty (PDF)"^^ . . . "Kauffeldt_Dissertation.pdf"^^ . . . "Strategic Interaction under Uncertainty (Other)"^^ . . . . . . "lightbox.jpg"^^ . . . "Strategic Interaction under Uncertainty (Other)"^^ . . . . . . "preview.jpg"^^ . . . "Strategic Interaction under Uncertainty (Other)"^^ . . . . . . "medium.jpg"^^ . . . "Strategic Interaction under Uncertainty (Other)"^^ . . . . . . "small.jpg"^^ . . . "Strategic Interaction under Uncertainty (Other)"^^ . . . . . . "indexcodes.txt"^^ . . 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