Search results for 'probability' (try it on Scholar)

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  1. Niki Pfeifer & G. D. Kleiter (2010). The Conditional in Mental Probability Logic. In M. Oaksford & N. Chater (eds.), Cognition and Conditionals: Probability and Logic in Human Thought. Oxford University Press. 153--173.score: 27.0
    The present chapter describes a probabilistic framework of human reasoning. It is based on probability logic. While there are several approaches to probability logic, we adopt the coherence based approach.
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  2. Sylvia Wenmackers (2011). Philosophy of Probability: Foundations, Epistemology, and Computation. Dissertation, University of Groningenscore: 24.0
    This dissertation is a contribution to formal and computational philosophy. -/- In the first part, we show that by exploiting the parallels between large, yet finite lotteries on the one hand and countably infinite lotteries on the other, we gain insights in the foundations of probability theory as well as in epistemology. Case 1: Infinite lotteries. We discuss how the concept of a fair finite lottery can best be extended to denumerably infinite lotteries. The solution boils down to the (...)
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  3. Gustavo Cevolani, Vincenzo Crupi & Roberto Festa (2010). The Whole Truth About Linda: Probability, Verisimilitude and a Paradox of Conjunction. In Marcello D'Agostino, Federico Laudisa, Giulio Giorello, Telmo Pievani & Corrado Sinigaglia (eds.), New Essays in Logic and Philosophy of Science. College Publications. 603--615.score: 24.0
    We provide a 'verisimilitudinarian' analysis of the well-known Linda paradox or conjunction fallacy, i.e., the fact that most people judge the probability of the conjunctive statement "Linda is a bank teller and is active in the feminist movement" (B & F) as more probable than the isolated statement "Linda is a bank teller" (B), contrary to an uncontroversial principle of probability theory. The basic idea is that experimental participants may judge B & F a better hypothesis about Linda (...)
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  4. Rani Lill Anjum, Johan Arnt Myrstad & Stephen Mumford, Conditional Probability From an Ontological Point of View.score: 24.0
    This paper argues that the technical notion of conditional probability, as given by the ratio analysis, is unsuitable for dealing with our pretheoretical and intuitive understanding of both conditionality and probability. This is an ontological account of conditionals that include an irreducible dispositional connection between the antecedent and consequent conditions and where the conditional has to be treated as an indivisible whole rather than compositional. The relevant type of conditionality is found in some well-defined group of conditional statements. (...)
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  5. Seth Yalcin (2010). Probability Operators. Philosophy Compass 5 (11):916-37.score: 24.0
    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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  6. Alastair Wilson (2012). Objective Probability in Everettian Quantum Mechanics. British Journal for the Philosophy of Science 64 (4):axs022.score: 24.0
    David Wallace has given a decision-theoretic argument for the Born Rule in the context of Everettian quantum mechanics (EQM). This approach promises to resolve some long-standing problems with probability in EQM, but it has faced plenty of resistance. One kind of objection (the ‘incoherence problem’) charges that the requisite notion of decision-theoretic uncertainty is unavailable in the Everettian picture, so that the argument cannot gain any traction; another kind of objection grants the proof’s applicability and targets the premises. In (...)
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  7. Sylvia Wenmackers, Danny E. P. Vanpoucke & Igor Douven (2012). Probability of Inconsistencies in Theory Revision. European Physical Journal B 85 (1):44 (15).score: 24.0
    We present a model for studying communities of epistemically interacting agents who update their belief states by averaging (in a specified way) the belief states of other agents in the community. The agents in our model have a rich belief state, involving multiple independent issues which are interrelated in such a way that they form a theory of the world. Our main goal is to calculate the probability for an agent to end up in an inconsistent belief state due (...)
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  8. Federica Russo (2006). Salmon and Van Fraassen on the Existence of Unobservable Entities: A Matter of Interpretation of Probability. [REVIEW] Foundations of Science 11 (3):221-247.score: 24.0
    A careful analysis of Salmon’s Theoretical Realism and van Fraassen’s Constructive Empiricism shows that both share a common origin: the requirement of literal construal of theories inherited by the Standard View. However, despite this common starting point, Salmon and van Fraassen strongly disagree on the existence of unobservable entities. I argue that their different ontological commitment towards the existence of unobservables traces back to their different views on the interpretation of probability via different conceptions of induction. In fact, inferences (...)
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  9. Patrick Maher (2010). Bayesian Probability. Synthese 172 (1):119 - 127.score: 24.0
    Bayesian decision theory is here construed as explicating a particular concept of rational choice and Bayesian probability is taken to be the concept of probability used in that theory. Bayesian probability is usually identified with the agent’s degrees of belief but that interpretation makes Bayesian decision theory a poor explication of the relevant concept of rational choice. A satisfactory conception of Bayesian decision theory is obtained by taking Bayesian probability to be an explicatum for inductive (...) given the agent’s evidence. (shrink)
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  10. Aidan Lyon (2010). Deterministic Probability: Neither Chance nor Credence. Synthese 182 (3):413-432.score: 24.0
    Some have argued that chance and determinism are compatible in order to account for the objectivity of probabilities in theories that are compatible with determinism, like Classical Statistical Mechanics (CSM) and Evolutionary Theory (ET). Contrarily, some have argued that chance and determinism are incompatible, and so such probabilities are subjective. In this paper, I argue that both of these positions are unsatisfactory. I argue that the probabilities of theories like CSM and ET are not chances, but also that they are (...)
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  11. Alan Clune (2011). Deeper Problems for Noonan's Probability Argument Against Abortion: On a Charitable Reading of Noonan's Conception Criterion of Humanity. Bioethics 25 (5):280-289.score: 24.0
    In ‘An Almost Absolute Value in History’ John T. Noonan criticizes several attempts to provide a criterion for when an entity deserves rights. These criteria, he argues are either arbitrary or lead to absurd consequence. Noonan proposes human conception as the criterion of rights, and justifies it by appeal to the sharp shift in probability, at conception, of becoming a being possessed of human reason. Conception, then, is when abortion becomes immoral.The article has an historical and a philosophical goal. (...)
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  12. Vieri Benci, Leon Horsten & Sylvia Wenmackers (2013). Non-Archimedean Probability. Milan Journal of Mathematics 81 (1):121-151.score: 24.0
    We propose an alternative approach to probability theory closely related to the framework of numerosity theory: non-Archimedean probability (NAP). In our approach, unlike in classical probability theory, all subsets of an infinite sample space are measurable and only the empty set gets assigned probability zero (in other words: the probability functions are regular). We use a non-Archimedean field as the range of the probability function. As a result, the property of countable additivity in Kolmogorov’s (...)
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  13. Isaac Levi (2010). Probability Logic, Logical Probability, and Inductive Support. Synthese 172 (1):97 - 118.score: 24.0
    This paper seeks to defend the following conclusions: The program advanced by Carnap and other necessarians for probability logic has little to recommend it except for one important point. Credal probability judgments ought to be adapted to changes in evidence or states of full belief in a principled manner in conformity with the inquirer’s confirmational commitments—except when the inquirer has good reason to modify his or her confirmational commitment. Probability logic ought to spell out the constraints on (...)
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  14. Jennifer S. Trueblood & Jerome R. Busemeyer (2011). A Quantum Probability Account of Order Effects in Inference. Cognitive Science 35 (8):1518-1552.score: 24.0
    Order of information plays a crucial role in the process of updating beliefs across time. In fact, the presence of order effects makes a classical or Bayesian approach to inference difficult. As a result, the existing models of inference, such as the belief-adjustment model, merely provide an ad hoc explanation for these effects. We postulate a quantum inference model for order effects based on the axiomatic principles of quantum probability theory. The quantum inference model explains order effects by transforming (...)
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  15. Han Geurdes, Quantum Mechanical EPRBA Covariance and Classical Probability.score: 24.0
    Contrary to Bell’s theorem it is demonstrated that with the use of classical probability theory the quantum correlation can be approximated. Hence, one may not conclude from experiment that all local hidden variable theories are ruled out by a violation of inequality result.
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  16. Masanari Asano, Irina Basieva, Andrei Khrennikov, Masanori Ohya & Ichiro Yamato (2013). Non-Kolmogorovian Approach to the Context-Dependent Systems Breaking the Classical Probability Law. Foundations of Physics 43 (7):895-911.score: 24.0
    There exist several phenomena breaking the classical probability laws. The systems related to such phenomena are context-dependent, so that they are adaptive to other systems. In this paper, we present a new mathematical formalism to compute the joint probability distribution for two event-systems by using concepts of the adaptive dynamics and quantum information theory, e.g., quantum channels and liftings. In physics the basic example of the context-dependent phenomena is the famous double-slit experiment. Recently similar examples have been found (...)
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  17. Jacintho Del Vecchio Junior, When Mathematics Touches Physics: Henri Poincaré on Probability.score: 24.0
    Probability plays a crucial role regarding the understanding of the relationship which exists between mathematics and physics. It will be the point of departure of this brief reflection concerning this subject, as well as about the placement of Poincaré’s thought in the scenario offered by some contemporary perspectives.
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  18. Branden Fitelson (2010). Pollock on Probability in Epistemology. [REVIEW] Philosophical Studies 148 (3):455 - 465.score: 24.0
    In Thinking and Acting John Pollock offers some criticisms of Bayesian epistemology, and he defends an alternative understanding of the role of probability in epistemology. Here, I defend the Bayesian against some of Pollock's criticisms, and I discuss a potential problem for Pollock's alternative account.
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  19. Patrick Suppes (2010). The Nature of Probability. Philosophical Studies 147 (1):89 - 102.score: 24.0
    The thesis of this article is that the nature of probability is centered on its formal properties, not on any of its standard interpretations. Section 2 is a survey of Bayesian applications. Section 3 focuses on two examples from physics that seem as completely objective as other physical concepts. Section 4 compares the conflict between subjective Bayesians and objectivists about probability to the earlier strident conflict in physics about the nature of force. Section 5 outlines a pragmatic approach (...)
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  20. Louis Vervoort, The Concept of Probability in Physics: An Analytic Version of von Mises’ Interpretation.score: 24.0
    In the following we will investigate whether von Mises’ frequency interpretation of probability can be modified to make it philosophically acceptable. We will reject certain elements of von Mises’ theory, but retain others. In the interpretation we propose we do not use von Mises’ often criticized ‘infinite collectives’ but we retain two essential claims of his interpretation, stating that probability can only be defined for events that can be repeated in similar conditions, and that exhibit frequency stabilization. The (...)
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  21. Roman Frič & Martin Papčo (2010). A Categorical Approach to Probability Theory. Studia Logica 94 (2):215 - 230.score: 24.0
    First, we discuss basic probability notions from the viewpoint of category theory. Our approach is based on the following four “sine quibus non” conditions: 1. (elementary) category theory is efficient (and suffices); 2. random variables, observables, probability measures, and states are morphisms; 3. classical probability theory and fuzzy probability theory in the sense of S. Gudder and S. Bugajski are special cases of a more general model; 4. a good model allows natural modifications.
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  22. Jeanne Peijnenburg (2012). A Case of Confusing Probability and Confirmation. Synthese 184 (1):101-107.score: 24.0
    Tom Stoneham put forward an argument purporting to show that coherentists are, under certain conditions, committed to the conjunction fallacy. Stoneham considers this argument a reductio ad absurdum of any coherence theory of justification. I argue that Stoneham neglects the distinction between degrees of confirmation and degrees of probability. Once the distinction is in place, it becomes clear that no conjunction fallacy has been committed.
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  23. E. G. Beltrametti & S. Bugajski (2002). Quantum Mechanics and Operational Probability Theory. Foundations of Science 7 (1-2):197-212.score: 24.0
    We discuss a generalization of the standard notion of probability space and show that the emerging framework, to be called operational probability theory, can be considered as underlying quantal theories. The proposed framework makes special reference to the convex structure of states and to a family of observables which is wider than the familiar set of random variables: it appears as an alternative to the known algebraic approach to quantum probability.
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  24. Theodore Hailperin (2000). Probability Semantics for Quantifier Logic. Journal of Philosophical Logic 29 (2):207-239.score: 24.0
    By supplying propositional calculus with a probability semantics we showed, in our 1996, that finite stochastic problems can be treated by logic-theoretic means equally as well as by the usual set-theoretic ones. In the present paper we continue the investigation to further the use of logical notions in probability theory. It is shown that quantifier logic, when supplied with a probability semantics, is capable of treating stochastic problems involving countably many trials.
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  25. Margarita A. Man’ko & Vladimir I. Man’ko (2011). Probability Description and Entropy of Classical and Quantum Systems. Foundations of Physics 41 (3):330-344.score: 24.0
    Tomographic approach to describing both the states in classical statistical mechanics and the states in quantum mechanics using the fair probability distributions is reviewed. The entropy associated with the probability distribution (tomographic entropy) for classical and quantum systems is studied. The experimental possibility to check the inequalities like the position–momentum uncertainty relations and entropic uncertainty relations are considered.
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  26. Josef Schurz (2007). Probability and Evolution. Why the Probability Argument of Creationists is Wrong. Journal for General Philosophy of Science 38 (1):163 - 165.score: 24.0
    Evolution is a time process. It proceeds in steps of definite length. The probability of each step is relatively high, so self organization of complex systems will be possible in finite time. Prerequisite for such a process is a selection rule, which certainly exists in evolution. Therefore, it would be wrong to calculate the probability of the formation of a complex system solely on the basis of the number of its components and as a momentary event.
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  27. Donald Bamber (2000). Entailment with Near Surety of Scaled Assertions of High Conditional Probability. Journal of Philosophical Logic 29 (1):1-74.score: 24.0
    An assertion of high conditional probability or, more briefly, an HCP assertion is a statement of the type: The conditional probability of B given A is close to one. The goal of this paper is to construct logics of HCP assertions whose conclusions are highly likely to be correct rather than certain to be correct. Such logics would allow useful conclusions to be drawn when the premises are not strong enough to allow conclusions to be reached with certainty. (...)
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  28. Lennart Åqvist (2007). An Interpretation of Probability in the Law of Evidence Based on Pro-Et-Contra Argumentation. Artificial Intelligence and Law 15 (4):391-410.score: 24.0
    The purpose of this paper is to improve on the logical and measure-theoretic foundations for the notion of probability in the law of evidence, which were given in my contributions Åqvist [ (1990) Logical analysis of epistemic modality: an explication of the Bolding–Ekelöf degrees of evidential strength. In: Klami HT (ed) Rätt och Sanning (Law and Truth. A symposium on legal proof-theory in Uppsala May 1989). Iustus Förlag, Uppsala, pp 43–54; (1992) Towards a logical theory of legal evidence: semantic (...)
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  29. Darrell P. Rowbottom (2013). Group Level Interpretations of Probability: New Directions. Pacific Philosophical Quarterly 94 (2):188-203.score: 24.0
    In this article, I present some new group level interpretations of probability, and champion one in particular: a consensus-based variant where group degrees of belief are construed as agreed upon betting quotients rather than shared personal degrees of belief. One notable feature of the account is that it allows us to treat consensus between experts on some matter as being on the union of their relevant background information. In the course of the discussion, I also introduce a novel distinction (...)
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  30. Robert Northcott (2010). Natural-Born Deterministe: A New Defense of Causation as Probability-Raising. Philosophical Studies 150 (1):1 - 20.score: 24.0
    A definition of causation as probability-raising is threatened by two kinds of counterexample: first, when a cause lowers the probability of its effect; and second, when the probability of an effect is raised by a non-cause. In this paper, I present an account that deals successfully with problem cases of both these kinds. In doing so, I also explore some novel implications of incorporating into the metaphysical investigation considerations of causal psychology.
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  31. Daniel Rothschild, Conditionals and Probability: A Classical Approach.score: 24.0
    Draft of a paper for the Sinn und Bedeutung 14 conference. Explains how to capture the link between conditionals the probability of indicative conditionals and conditional probability using a classical semantics for conditionals. (Note: some introductory material is shared with a twin paper, "Capturing the Relationship Between Conditionals and Conditional Probability with a Trivalent Semantics".).
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  32. Charis Anastopoulos (2006). Classical Versus Quantum Probability in Sequential Measurements. Foundations of Physics 36 (11):1601-1661.score: 24.0
    We demonstrate in this paper that the probabilities for sequential measurements have features very different from those of single-time measurements. First, they cannot be modelled by a classical stochastic process. Second, they are contextual, namely they depend strongly on the specific measurement scheme through which they are determined. We construct Positive-Operator-Valued measures (POVM) that provide such probabilities. For observables with continuous spectrum, the constructed POVMs depend strongly on the resolution of the measurement device, a conclusion that persists even if we (...)
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  33. Jonas Clausen Mork (2013). Uncertainty, Credal Sets and Second Order Probability. Synthese 190 (3):353-378.score: 24.0
    The last 20 years or so has seen an intense search carried out within Dempster–Shafer theory, with the aim of finding a generalization of the Shannon entropy for belief functions. In that time, there has also been much progress made in credal set theory—another generalization of the traditional Bayesian epistemic representation—albeit not in this particular area. In credal set theory, sets of probability functions are utilized to represent the epistemic state of rational agents instead of the single probability (...)
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  34. Horacio Arló Costa & Rohit Parikh (2005). Conditional Probability and Defeasible Inference. Journal of Philosophical Logic 34 (1):97 - 119.score: 24.0
    We offer a probabilistic model of rational consequence relations (Lehmann and Magidor, 1990) by appealing to the extension of the classical Ramsey-Adams test proposed by Vann McGee in (McGee, 1994). Previous and influential models of nonmonotonic consequence relations have been produced in terms of the dynamics of expectations (Gärdenfors and Makinson, 1994; Gärdenfors, 1993).'Expectation' is a term of art in these models, which should not be confused with the notion of expected utility. The expectations of an agent are some form (...)
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  35. Brian Weatherson (2003). From Classical to Intuitionistic Probability. Notre Dame Journal of Formal Logic 44 (2):111-123.score: 24.0
    We generalize the Kolmogorov axioms for probability calculus to obtain conditions defining, for any given logic, a class of probability functions relative to that logic, coinciding with the standard probability functions in the special case of classical logic but allowing consideration of other classes of "essentially Kolmogorovian" probability functions relative to other logics. We take a broad view of the Bayesian approach as dictating inter alia that from the perspective of a given logic, rational degrees of (...)
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  36. László E. Szabó (2007). Objective Probability-Like Things with and Without Objective Indeterminism. Studies in History and Philosophy of Science Part B 38 (3):626-634.score: 24.0
    I shall argue that there is no such property of an event as its “probability.” This is why standard interpretations cannot give a sound definition in empirical terms of what “probability” is, and this is why empirical sciences like physics can manage without such a definition. “Probability” is a collective term, the meaning of which varies from context to context: it means different — dimensionless [0, 1]-valued — physical quantities characterising the different particular situations. In other words, (...)
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  37. Fabio G. Cozman (2012). Sets of Probability Distributions, Independence, and Convexity. Synthese 186 (2):577-600.score: 24.0
    This paper analyzes concepts of independence and assumptions of convexity in the theory of sets of probability distributions. The starting point is Kyburg and Pittarelli’s discussion of “convex Bayesianism” (in particular their proposals concerning E-admissibility, independence, and convexity). The paper offers an organized review of the literature on independence for sets of probability distributions; new results on graphoid properties and on the justification of “strong independence” (using exchangeability) are presented. Finally, the connection between Kyburg and Pittarelli’s results and (...)
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  38. Peter Milne (2012). Probability as a Measure of Information Added. Journal of Logic, Language and Information 21 (2):163-188.score: 24.0
    Some propositions add more information to bodies of propositions than do others. We start with intuitive considerations on qualitative comparisons of information added . Central to these are considerations bearing on conjunctions and on negations. We find that we can discern two distinct, incompatible, notions of information added. From the comparative notions we pass to quantitative measurement of information added. In this we borrow heavily from the literature on quantitative representations of qualitative, comparative conditional probability. We look at two (...)
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  39. Maurizio Negri (2010). A Probability Measure for Partial Events. Studia Logica 94 (2):271 - 290.score: 24.0
    We introduce the concept of partial event as a pair of disjoint sets, respectively the favorable and the unfavorable cases. Partial events can be seen as a De Morgan algebra with a single fixed point for the complement. We introduce the concept of a measure of partial probability, based on a set of axioms resembling Kolmogoroff’s. Finally we define a concept of conditional probability for partial events and apply this concept to the analysis of the two-slit experiment in (...)
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  40. Gregg Jaeger (2012). Generalized Quantum Probability and Entanglement Enhancement Witnessing. Foundations of Physics 42 (6):752-759.score: 24.0
    It has been suggested (cf. Sinha et al. in Science 329:418, 2010) that the Born rule for quantum probability could be violated. It has also been suggested that, in a generalized version of quantum mechanical probability theory such as that proposed by Sorkin (Mod. Phys. Lett. A 9:3119, 1994) there might occur deviations from the predictions of quantum probability in cases where more than two paths are available to a self-interfering system. These would lead to additional contributions (...)
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  41. NG Yew-Kwang (2005). Intergenerational Impartiality: Replacing Discounting by Probability Weighting. [REVIEW] Journal of Agricultural and Environmental Ethics 18 (3):237-257.score: 24.0
    Intergenerational impartiality requires putting the welfare of future generations at par with that of our own. However, rational choice requires weighting all welfare values by the respective probabilities of realization. As the risk of non-survival of mankind is strictly positive for all time periods and as the probability of non-survival is cumulative, the probability weights operate like discount factors, though justified on a morally justifiable and completely different ground. Impartial intertemporal welfare maximization is acceptable, though the welfare of (...)
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  42. Marshall Abrams (2012). Mechanistic Probability. Synthese 187 (2):343-375.score: 24.0
    I describe a realist, ontologically objective interpretation of probability, "far-flung frequency (FFF) mechanistic probability". FFF mechanistic probability is defined in terms of facts about the causal structure of devices and certain sets of frequencies in the actual world. Though defined partly in terms of frequencies, FFF mechanistic probability avoids many drawbacks of well-known frequency theories and helps causally explain stable frequencies, which will usually be close to the values of mechanistic probabilities. I also argue that it's (...)
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  43. Jean Baratgin & Guy Politzer (2011). Updating: A Psychologically Basic Situation of Probability Revision. Thinking and Reasoning 16 (4):253-287.score: 24.0
    The Bayesian model has been used in psychology as the standard reference for the study of probability revision. In the first part of this paper we show that this traditional choice restricts the scope of the experimental investigation of revision to a stable universe. This is the case of a situation that, technically, is known as focusing. We argue that it is essential for a better understanding of human probability revision to consider another situation called updating (Katsuno & (...)
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  44. Vieri Benci, Leon Horsten & Sylvia Wenmackers (2012). Axioms for Non-Archimedean Probability (NAP). In De Vuyst J. & Demey L. (eds.), Future Directions for Logic; Proceedings of PhDs in Logic III - Vol. 2 of IfColog Proceedings. College Publications.score: 24.0
    In this contribution, we focus on probabilistic problems with a denumerably or non-denumerably infinite number of possible outcomes. Kolmogorov (1933) provided an axiomatic basis for probability theory, presented as a part of measure theory, which is a branch of standard analysis or calculus. Since standard analysis does not allow for non-Archimedean quantities (i.e. infinitesimals), we may call Kolmogorov's approach "Archimedean probability theory". We show that allowing non-Archimedean probability values may have considerable epistemological advantages in the infinite case. (...)
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  45. 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.score: 24.0
    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 (...)
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  46. Fred Kronz (2007). Non-Monotonic Probability Theory and Photon Polarization. Journal of Philosophical Logic 36 (4):449 - 472.score: 24.0
    A non-monotonic theory of probability is put forward and shown to have applicability in the quantum domain. It is obtained simply by replacing Kolmogorov's positivity axiom, which places the lower bound for probabilities at zero, with an axiom that reduces that lower bound to minus one. Kolmogorov's theory of probability is monotonic, meaning that the probability of A is less then or equal to that of B whenever A entails B. The new theory violates monotonicity, as its (...)
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  47. Niall Shanks (1993). Time and the Propensity Interpretation of Probability. Journal for General Philosophy of Science 24 (2):293 - 302.score: 24.0
    The prime concern of this paper is with the nature of probability. It is argued that questions concerning the nature of probability are intimately linked to questions about the nature of time. The case study here concerns the single case propensity interpretation of probability. It is argued that while this interpretation of probability has a natural place in the quantum theory, the metaphysical picture of time to be found in relativity theory is incompatible with such a (...)
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  48. Louis Vervoort (2013). Does Chance Hide Necessity ? A Reevaluation of the Debate ‘Determinism - Indeterminism’ in the Light of Quantum Mechanics and Probability Theory. Dissertation, University of Montrealscore: 24.0
    In this text the ancient philosophical question of determinism (“Does every event have a cause ?”) will be re-examined. In the philosophy of science and physics communities the orthodox position states that the physical world is indeterministic: quantum events would have no causes but happen by irreducible chance. Arguably the clearest theorem that leads to this conclusion is Bell’s theorem. The commonly accepted ‘solution’ to the theorem is ‘indeterminism’, in agreement with the Copenhagen interpretation. Here it is recalled that indeterminism (...)
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  49. Horacio Arló-Costa & Richmond H. Thomason (2001). Iterative Probability Kinematics. Journal of Philosophical Logic 30 (5):479-524.score: 24.0
    Following the pioneer work of Bruno De Finetti [12], conditional probability spaces (allowing for conditioning with events of measure zero) have been studied since (at least) the 1950's. Perhaps the most salient axiomatizations are Karl Popper's in [31], and Alfred Renyi's in [33]. Nonstandard probability spaces [34] are a well know alternative to this approach. Vann McGee proposed in [30] a result relating both approaches by showing that the standard values of infinitesimal probability functions are representable as (...)
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  50. Georg J. W. Dorn (1992/93). Popper’s Laws of the Excess of the Probability of the Conditional Over the Conditional Probability. Conceptus 26:3–61.score: 24.0
    Karl Popper discovered in 1938 that the unconditional probability of a conditional of the form ‘If A, then B’ normally exceeds the conditional probability of B given A, provided that ‘If A, then B’ is taken to mean the same as ‘Not (A and not B)’. So it was clear (but presumably only to him at that time) that the conditional probability of B given A cannot be reduced to the unconditional probability of the material conditional (...)
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