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  1. Alan Baker (2007). Putting Expectations in Order. Philosophy of Science 74 (5):692-700.
    In their paper, “Vexing Expectations,” Nover and Hájek (2004) present an allegedly paradoxical betting scenario which they call the Pasadena Game (PG). They argue that the silence of standard decision theory concerning the value of playing PG poses a serious problem. This paper provides a threefold response. First, I argue that the real problem is not that decision theory is “silent” concerning PG, but that it delivers multiple conflicting verdicts. Second, I offer a diagnosis of the problem based on the (...)
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  2. David J. Chalmers (2002). The St. Petersburg Two-Envelope Paradox. Analysis 62 (274):155–157.
    I reason: (1) For any x, if I knew that A contained x, then the odds are even that B contains either 2x or x/2, so the expected amount in B would be 5x/4. So (2) for all x, if I knew that A contained x, I would have an expected gain in switching to B. So (3) I should switch to B. But this seems clearly wrong, as my information about A and B is symmetrical.
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  3. Mark Colyvan (2008). Relative Expectation Theory. Journal of Philosophy 105 (1):37-44.
    Games such as the St. Petersburg game present serious problems for decision theory.1 The St. Petersburg game invokes an unbounded utility function to produce an infinite expectation for playing the game. The problem is usually presented as a clash between decision theory and intuition: most people are not prepared to pay a large finite sum to buy into this game, yet this is precisely what decision theory suggests we ought to do. But there is another problem associated with the St. (...)
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  4. Terrence L. Fine (2008). Evaluating the Pasadena, Altadena, and St Petersburg Gambles. Mind 117 (467):613-632.
    By recourse to the fundamentals of preference orderings and their numerical representations through linear utility, we address certain questions raised in Nover and Hájek 2004, Hájek and Nover 2006, and Colyvan 2006. In brief, the Pasadena and Altadena games are well-defined and can be assigned any finite utility values while remaining consistent with preferences between those games having well-defined finite expected value. This is also true for the St Petersburg game. Furthermore, the dominance claimed for the Altadena game over the (...)
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  5. Alan Hájek (2006). In Memory of Richard Jeffrey: Some Reminiscences and Some Reflections onThe Logic of Decision. Philosophy of Science 73 (5):947-958.
    This paper is partly a tribute to Richard Jeffrey, partly a reflection on some of his writings, The Logic of Decision in particular. I begin with a brief biography and some fond reminiscences of Dick. I turn to some of the key tenets of his version of Bayesianism. All of these tenets are deployed in my discussion of his response to the St. Petersburg paradox, a notorious problem for decision theory that involves a game of infinite expectation. Prompted by that (...)
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  6. Alan Hájek & Harris Nover (2008). Complex Expectations. Mind 117 (467):643 - 664.
    In our 2004, we introduced two games in the spirit of the St Petersburg game, the Pasadena and Altadena games. As these latter games lack an expectation, we argued that they pose a paradox for decision theory. Terrence Fine has shown that any finite valuations for the Pasadena, Altadena, and St Petersburg games are consistent with the standard decision-theoretic axioms. In particular, one can value the Pasadena game above the other two, a result that conflicts with both our intuitions and (...)
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  7. Jeff Jordan (1994). The St. Petersburg Paradox and Pascal's Wager. Philosophia 23 (1-4):207-222.
  8. Amos Nathan (1984). False Expectations. Philosophy of Science 51 (1):128-136.
    Common probabilistic fallacies and putative paradoxes are surveyed, including those arising from distribution repartitioning, from the reordering of expectation series, and from misconceptions regarding expected and almost certain gains in games of chance. Conditions are given for such games to be well-posed. By way of example, Bernoulli's "Petersburg Paradox" and Hacking's "Strange Expectations" are discussed and the latter are resolved. Feller's generalized "fair price, in the classical sense" is critically reviewed.
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  9. Martin Peterson (2011). A New Twist to the St. Petersburg Paradox. Journal of Philosophy 108 (12):697-699.
    In this paper I add a new twist to Colyvan's version of the Petrograd paradox.
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  10. Marie Pfiffelmann (2011). Solving the St. Petersburg Paradox in Cumulative Prospect Theory: The Right Amount of Probability Weighting. Theory and Decision 71 (3):325-341.
    Cumulative Prospect Theory (CPT) does not explain the St. Petersburg Paradox. We show that the solutions related to probability weighting proposed to solve this paradox, (Blavatskyy, Management Science 51:677–678, 2005; Rieger and Wang, Economic Theory 28:665–679, 2006) have to cope with limitations. In that framework, CPT fails to accommodate both gambling and insurance behavior. We suggest replacing the weighting functions generally proposed in the literature by another specification which respects the following properties: (1) to solve the paradox, the slope at (...)
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  11. Teddy Seidenfeld, Mark J. Schervish & Joseph B. Kadane, Preference for Equivalent Random Variables: A Price for Unbounded Utilities.
    When real-valued utilities for outcomes are bounded, or when all variables are simple, it is consistent with expected utility to have preferences defined over probability distributions or lotteries. That is, under such circumstances two variables with a common probability distribution over outcomes – equivalent variables – occupy the same place in a preference ordering. However, if strict preference respects uniform, strict dominance in outcomes between variables, and if indifference between two variables entails indifference between their difference and the status quo, (...)
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  12. David Teira (2006). On the Normative Dimension of St. Petersburg Paradox. Studies in History and Philosophy of Science 37 (2):210-23.
    In this paper I offer an account of the normative dimension implicit in D. Bernoulli’s expected utility functions by means of an analysis of the juridical metaphors upon which the concept of mathematical expectation was moulded. Following a suggestion by the late E. Coumet, I show how this concept incorporated a certain standard of justice which was put in question by the St. Petersburg paradox. I contend that Bernoulli would have solved it by introducing an alternative normative criterion rather than (...)
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  13. Mariam Thalos & Oliver Richardson (2014). Capitalization in the St. Petersburg Game Why Statistical Distributions Matter. Politics, Philosophy and Economics 13 (3):292-313.
    In spite of its infinite expectation value, the St. Petersburg game is not only a gamble without supply in the real world, but also one without demand at apparently very reasonable asking prices. We offer a rationalizing explanation of why the St. Petersburg bargain is unattractive on both sides (to both house and player) in the mid-range of prices (finite but upwards of about $4). Our analysis – featuring (1) the already-established fact that the average of finite ensembles of the (...)
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