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  1.  21
    Completeness for Counter-Doxa Conditionals – Using Ranking Semantics.Eric Raidl - 2019 - Review of Symbolic Logic 12 (4):861-891.
    Standard conditionals $\varphi > \psi$, by which I roughly mean variably strict conditionals à la Stalnaker and Lewis, are trivially true for impossible antecedents. This article investigates three modifications in a doxastic setting. For the neutral conditional, all impossible-antecedent conditionals are false, for the doxastic conditional they are only true if the consequent is absolutely necessary, and for the metaphysical conditional only if the consequent is ‘model-implied’ by the antecedent. I motivate these conditionals logically, and also doxastically by properties of (...)
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  2.  39
    Open-Minded Orthodox Bayesianism by Epsilon-Conditionalization.Eric Raidl - 2020 - British Journal for the Philosophy of Science 71 (1):139-176.
    Orthodox Bayesianism endorses revising by conditionalization. This paper investigates the zero-raising problem, or equivalently the certainty-dropping problem of orthodox Bayesianism: previously neglected possibilities remain neglected, although the new evidence might suggest otherwise. Yet, one may want to model open-minded agents, that is, agents capable of raising previously neglected possibilities. Different reasons can be given for open-mindedness, one of which is fallibilism. The paper proposes a family of open-minded propositional revisions depending on a parameter ϵ. The basic idea is this: first (...)
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  3.  38
    Bridging Ranking Theory and the Stability Theory of Belief.Eric Raidl & Niels Skovgaard-Olsen - 2017 - Journal of Philosophical Logic 46 (6):577-609.
    In this paper we compare Leitgeb’s stability theory of belief and Spohn’s ranking-theoretic account of belief. We discuss the two theories as solutions to the lottery paradox. To compare the two theories, we introduce a novel translation between ranking functions and probability functions. We draw some crucial consequences from this translation, in particular a new probabilistic belief notion. Based on this, we explore the logical relation between the two belief theories, showing that models of Leitgeb’s theory correspond to certain models (...)
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  4.  16
    Quick Completeness for the Evidential Conditional.Eric Raidl - unknown
    Proves Completeness for the Evidential Conditional.
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  5.  4
    Definable Conditionals.Eric Raidl - forthcoming - Topoi.
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  6.  14
    Lewis’ Triviality for Quasi Probabilities.Eric Raidl - 2019 - Journal of Logic, Language and Information 28 (4):515-549.
    According to Stalnaker’s Thesis, the probability of a conditional is the conditional probability. Under some mild conditions, the thesis trivialises probabilities and conditionals, as initially shown by David Lewis. This article asks the following question: does still lead to triviality, if the probability function in is replaced by a probability-like function? The article considers plausibility functions, in the sense of Friedman and Halpern, which additionally mimic probabilistic additivity and conditionalisation. These quasi probabilities comprise Friedman–Halpern’s conditional plausibility spaces, as well as (...)
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  7.  10
    An Accuracy Argument in Favor of Ranking Theory.Eric Raidl & Wolfgang Spohn - 2020 - Journal of Philosophical Logic 49 (2):283-313.
    Fitelson and McCarthy have proposed an accuracy measure for confidence orders which favors probability measures and Dempster-Shafer belief functions as accounts of degrees of belief and excludes ranking functions. Their accuracy measure only penalizes mistakes in confidence comparisons. We propose an alternative accuracy measure that also rewards correct confidence comparisons. Thus we conform to both of William James’ maxims: “Believe truth! Shun error!” We combine the two maxims, penalties and rewards, into one criterion that we call prioritized accuracy optimization. That (...)
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  8. Cheating at Coin Tossing.Eric Raidl - unknown
    Arguments for A "fair" coin has probability 1/2. There is no physical probability attached to the coin, we can cheat on each toss (by sufficient control). My aim: The coin toss is fine-grained deterministic, but coarsgrained random.
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  9.  9
    Epistemic-State Parallelism: Translating Between Probabilities and Ranks.Eric Raidl - forthcoming - Erkenntnis:1-28.
    This paper contributes to the investigation of the nature of the relation between probability theory and ranking theory. The paper aims at explaining the structural harmony between the laws of probability theory and those of ranking theory in a way that respects the foundational dualistic attitude developed by Spohn in The Laws of Belief. The paper argues that the so called atomic translation family satisfies the desiderata and does so in the ‘best’ possible way. On the one hand, the atomic (...)
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  10.  9
    Updating a Progic.Eric Raidl - 2016 - Journal of Applied Logic 14:65-94.