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Philosophy of Probability, Misc

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  1. Sorin Bangu (2010). On Bertrand's Paradox. Analysis 70 (1):30-35.
    The Principle of Indifference is a central element of the ‘classical’ conception of probability, but, for all its strong intuitive appeal, it is widely believed that it faces a devastating objection: the so-called (by Poincare´) ‘Bertrand paradoxes’ (in essence, cases in which the same probability question receives different answers). The puzzle has fascinated many since its discovery, and a series of clever solutions (followed promptly by equally clever rebuttals) have been proposed. However, despite the long-standing interest in this problem, an (...)
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  2. Antony Eagle, Chance Versus Randomness. Stanford Encyclopedia of Philosophy.
    This article explores the connection between objective chance and the randomness of a sequence of outcomes. Discussion is focussed around the claim that something happens by chance iff it is random. This claim is subject to many objections. Attempts to save it by providing alternative theories of chance and randomness, involving indeterminism, unpredictability, and reductionism about chance, are canvassed. The article is largely expository, with particular attention being paid to the details of algorithmic randomness, a topic relatively unfamiliar to philosophers.
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  3. Antony Eagle (2005). Randomness Is Unpredictability. British Journal for the Philosophy of Science 56 (4):749 - 790.
    The concept of randomness has been unjustly neglected in recent philosophical literature, and when philosophers have thought about it, they have usually acquiesced in views about the concept that are fundamentally flawed. After indicating the ways in which these accounts are flawed, I propose that randomness is to be understood as a special case of the epistemic concept of the unpredictability of a process. This proposal arguably captures the intuitive desiderata for the concept of randomness; at least it should suggest (...)
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  4. Ellery Eells, Brian Skyrms & Ernest W. Adams (1994). Probability and Conditionals: Belief Revision and Rational Decision. Cambridge University Press.
    This is a 'state of the art' collection of essays on the relation between probabilities, especially conditional probabilities, and conditionals. It provides new negative results which sharply limit the ways conditionals can be related to conditional probabilities. There are also positive ideas and results which will open up new areas of research. The collection is intended to honour Ernest W. Adams, whose seminal work is largely responsible for creating this area of inquiry. As well as describing, evaluating, and applying Adams' (...)
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  5. Branden Fitelson & Lara Buchak, Separability Assumptions in Scoring-Rule-Based Arguments for Probabilism.
    - In decision theory, an agent is deciding how to value a gamble that results in different outcomes in different states. Each outcome gets a utility value for the agent.
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  6. Shan Gao, The Wave Function and Its Evolution.
    The meaning of the wave function and its evolution are investigated. First, we argue that the wave function in quantum mechanics is a description of random discontinuous motion of particles, and the modulus square of the wave function gives the probability density of the particles being in certain locations in space. Next, we show that the linear non-relativistic evolution of the wave function of an isolated system obeys the free Schrödinger equation due to the requirements of spacetime translation invariance and (...)
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  7. Shan Gao, Protective Measurement and the Meaning of the Wave Function.
    This article analyzes the implications of protective measurement for the meaning of the wave function. According to protective measurement, a charged quantum system has mass and charge density proportional to the modulus square of its wave function. It is shown that the mass and charge density is not real but effective, formed by the ergodic motion of a localized particle with the total mass and charge of the system. Moreover, it is argued that the ergodic motion is not continuous but (...)
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  8. Shan Gao, Derivation of the Meaning of the Wave Function.
    We show that the physical meaning of the wave function can be derived based on the established parts of quantum mechanics. It turns out that the wave function represents the state of random discontinuous motion of particles, and its modulus square determines the probability density of the particles appearing in certain positions in space.
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  9. D. Gillies (2006). Maria Carla Galavotti. Philosophical Introduction to Probability. Stanford: Center for the Study of Language and Information Publications, 2005. Pp. X + 265. ISBN 1-57586-490-8 (Pbk), 1-57586-489-4 (Hardback). Philosophia Mathematica 15 (1):129-132.
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  10. Sven Ove Hansson (2009). From the Casino to the Jungle. Synthese 168 (3):423 - 432.
    Clear-cut cases of decision-making under risk (known probabilities) are unusual in real life. The gambler’s decisions at the roulette table are as close as we can get to this type of decision-making. In contrast, decision-making under uncertainty (unknown probabilities) can be exemplified by a decision whether to enter a jungle that may contain unknown dangers. Life is usually more like an expedition into an unknown jungle than a visit to the casino. Nevertheless, it is common in decision-supporting disciplines to proceed (...)
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  11. James Hawthorne (2004). Three Models of Sequential Belief Updating on Uncertain Evidence. Journal of Philosophical Logic 33 (1):89-123.
    Jeffrey updating is a natural extension of Bayesian updating to cases where the evidence is uncertain. But, the resulting degrees of belief appear to be sensitive to the order in which the uncertain evidence is acquired, a rather un-Bayesian looking effect. This order dependence results from the way in which basic Jeffrey updating is usually extended to sequences of updates. The usual extension seems very natural, but there are other plausible ways to extend Bayesian updating that maintain order-independence. I will (...)
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  12. James Hawthorne (2004). Three Models of Sequential Belief Updating on Uncertain Evidence. Journal of Philosophical Logic 33 (1):89-123.
    Jeffrey updating is a natural extension of Bayesian updating to cases where the evidence is uncertain. But, the resulting degrees of belief appear to be sensitive to the order in which the uncertain evidence is acquired, a rather un-Bayesian looking effect. This order dependence results from the way in which basic Jeffrey updating is usually extended to sequences of updates. The usual extension seems very natural, but there are other plausible ways to extend Bayesian updating that maintain order-independence. I will (...)
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  13. James Hawthorne (1996). On the Logic of Nonmonotonic Conditionals and Conditional Probabilities. Journal of Philosophical Logic 25 (2):185-218.
    I will describe the logics of a range of conditionals that behave like conditional probabilities at various levels of probabilistic support. Families of these conditionals will be characterized in terms of the rules that their members obey. I will show that for each conditional, , in a given family, there is a probabilistic support level r and a conditional probability function P such that, for all sentences C and B, C->B holds just in case P[B|C] is greater than or equal (...)
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  14. Niki Pfeifer & G. D. Kleiter (2009). Framing Human Inference by Coherence Based Probability Logic. Journal of Applied Logic 7 (2):206--217.
  15. Niki Pfeifer & G. D. Kleiter (2006). Inference in Conditional Probability Logic. Kybernetika 42 (2):391--404.
    An important field of probability logic is the investigation of inference rules that propagate point probabilities or, more generally, interval probabilities from premises to conclusions. Conditional probability logic (CPL) interprets the common sense expressions of the form “if . . . , then . . . ” by conditional probabilities and not by the probability of the material implication. An inference rule is probabilistically informative if the coherent probability interval of its conclusion is not necessarily equal to the unit interval (...)
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  16. Niki Pfeifer & G. D. Kleiter (2006). Towards a Probability Logic Based on Statistical Reasoning. In Proceedings of the 11 T H Ipmu International Conference (Information Processing and Management of Uncertainty in Knowledge-Based Systems).
    Logical argument forms are investigated by second order probability density functions. When the premises are expressed by beta distributions, the conclusions usually are mixtures of beta distributions. If the shape parameters of the distributions are assumed to be additive (natural sampling), then the lower and upper bounds of the mixing distributions (P´olya-Eggenberger distributions) are parallel to the corresponding lower and upper probabilities in conditional probability logic.
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  17. Niki Pfeifer & G. D. Kleiter (2005). Towards a Mental Probability Logic. Psychologica Belgica 45 (1):71--99.
    We propose probability logic as an appropriate standard of reference for evaluating human inferences. Probability logical accounts of nonmonotonic reasoning with system p, and conditional syllogisms (modus ponens, etc.) are explored. Furthermore, we present categorical syllogisms with intermediate quantifiers, like the “most . . . ” quantifier. While most of the paper is theoretical and intended to stimulate psychological studies, we summarize our empirical studies on human nonmonotonic reasoning.
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  18. Huw Price, The Lion, the 'Which?' And the Wardrobe -- Reading Lewis as a Closet One-Boxer.
    Newcomb problems turn on a tension between two principles of choice: roughly, a principle sensitive to the causal features of the relevant situation, and a principle sensitive only to evidential factors. Two-boxers give priority to causal beliefs, and one-boxers to evidential beliefs. A similar issue can arise when the modality in question is chance, rather than causation. In this case, the conflict is between decision rules based on credences guided solely by chances, and rules based on credences guided by other (...)
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  19. Andrew Sepielli (forthcoming). Normative Uncertainty for Non-Cognitivists. Philosophical Studies.
    Normative judgments involve two gradable features. First, the judgments themselves can come in degrees; second, the strength of reasons represented in the judgments can come in degrees. Michael Smith has argued that non-cognitivism cannot accommodate both of these gradable dimensions. The degrees of a non-cognitive state can stand in for degrees of judgment, or degrees of reason strength represented in judgment, but not both. I argue that (a) there are brands of noncognitivism that can surmount Smith’s challenge, and (b) any (...)
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  20. Michael J. Shaffer (2004). Probability and Tempered Modal Eliminativism. History and Philosophy of Logic 25 (4):305-318.
    In this paper the strategy for the eliminative reduction of the alethic modalities suggested by John Venn is outlined and it is shown to anticipate certain related contemporary empiricistic and nominalistic projects. Venn attempted to reduce the alethic modalities to probabilities, and thus suggested a promising solution to the nagging issue of the inclusion of modal statements in empiricistic philosophical systems. However, despite the promise that this suggestion held for laying the ‘ghost of modality’ to rest, this general approach, tempered (...)
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  21. Eric Swanson (2009). How Not to Theorize About the Language of Subjective Uncertainty. In Andy Egan & B. Weatherson (eds.), Epistemic Modality. Oxford University Press.
    A successful theory of the language of subjective uncertainty would meet several important constraints. First, it would explain how use of the language of subjective uncertainty affects addressees’ states of subjective uncertainty. Second, it would explain how such use affects what possibilities are treated as live for purposes of conversation. Third, it would accommodate 'quantifying in' to the scope of epistemic modals. Fourth, it would explain the norms governing the language of subjective uncertainty, and the differences between them and the (...)
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  22. Nassim N. Taleb, The Future Has Thicker Tails Than the Past: Model Error as Branching Counterfactuals.
    Ex ante predicted outcomes should be interpreted as counterfactuals (potential histories), with errors as the spread between outcomes. But error rates have error rates. We reapply measurements of uncertainty about the estimation errors of the estimation errors of an estimation treated as branching counterfactuals. Such recursions of epistemic uncertainty have markedly different distributial properties from conventional sampling error, and lead to fatter tails in the projections than in past realizations. Counterfactuals of error rates always lead to fat tails, regardless of (...)
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  23. J. R. G. Williams, Gradational Accuracy and Non-Classical Semantics.
    Joyce (1998) gives an argument for probabilism: the doctrine that rational credences should conform to the axioms of probability. In doing so, he provides a distinctive take on how the normative force of probabilism relates to the injunction to believe what is true. But Joyce presupposes that the truth values of the propositions over which credences are defined are classical. I generalize the core of Joyce’s argument to remove this presupposition. On the same assumptions as Joyce uses, the credences of (...)
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  24. Seth Yalcin (2010). Probability Operators. Philosophy Compass 5 (11):916-37.
    This is a study in the meaning of natural language probability operators, sentential operators such as probably and likely. We ask what sort of formal structure is required to model the logic and semantics of these operators. Along the way we investigate their deep connections to indicative conditionals and epistemic modals, probe their scalar structure, observe their sensitivity to contex- tually salient contrasts, and explore some of their scopal idiosyncrasies.
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