10 found
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  1. The Bayesian and the Abductivist.Mattias Skipper & Olav Benjamin Vassend - forthcoming - Noûs.
    A major open question in the borderlands between epistemology and philosophy of science concerns whether Bayesian updating and abductive inference are compatible. Some philosophers—most influentially Bas van Fraassen—have argued that they are not. Others have disagreed, arguing that abduction, properly understood, is indeed compatible with Bayesianism. Here we present two formal results that allow us to tackle this question from a new angle. We start by formulating what we take to be a minimal version of the claim that abduction is (...)
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  2.  95
    Justifying the Norms of Inductive Inference.Olav Benjamin Vassend - 2022 - British Journal for the Philosophy of Science 73 (1):135-160.
    Bayesian inference is limited in scope because it cannot be applied in idealized contexts where none of the hypotheses under consideration is true and because it is committed to always using the likelihood as a measure of evidential favouring, even when that is inappropriate. The purpose of this article is to study inductive inference in a very general setting where finding the truth is not necessarily the goal and where the measure of evidential favouring is not necessarily the likelihood. I (...)
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  3.  89
    Why change your beliefs rather than your desires? Two puzzles.Olav Benjamin Vassend - 2021 - Analysis 81 (2):275-281.
    In standard decision theory, the probability function ought to be updated in light of evidence, but the utility function generally stays fixed. However, there is nothing in the formal theory that prevents one from instead updating the utility function, while keeping the probability function fixed. Moreover, there are good arguments for updating the utilities and not just the probabilities. Hence, the first puzzle is whether there is anything that justifies updating beliefs, but not desires, in light of evidence. The paper (...)
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  4.  75
    New Semantics for Bayesian Inference: The Interpretive Problem and Its Solutions.Olav Benjamin Vassend - 2019 - Philosophy of Science 86 (4):696-718.
    Scientists often study hypotheses that they know to be false. This creates an interpretive problem for Bayesians because the probability assigned to a hypothesis is typically interpreted as the probability that the hypothesis is true. I argue that solving the interpretive problem requires coming up with a new semantics for Bayesian inference. I present and contrast two new semantic frameworks, and I argue that both of them support the claim that there is pervasive pragmatic encroachment on whether a given Bayesian (...)
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  5.  51
    (1 other version)Confirmation and the ordinal equivalence thesis.Olav Benjamin Vassend - 2019 - Synthese 196 (3):1079-1095.
    According to a widespread but implicit thesis in Bayesian confirmation theory, two confirmation measures are considered equivalent if they are ordinally equivalent—call this the “ordinal equivalence thesis”. I argue that adopting OET has significant costs. First, adopting OET renders one incapable of determining whether a piece of evidence substantially favors one hypothesis over another. Second, OET must be rejected if merely ordinal conclusions are to be drawn from the expected value of a confirmation measure. Furthermore, several arguments and applications of (...)
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  6.  94
    Sometimes It Is Better to Do Nothing: A New Argument for Causal Decision Theory.Olav Benjamin Vassend - 2022 - Ergo: An Open Access Journal of Philosophy 9.
    It is often thought that the main significant difference between evidential decision theory and causal decision theory is that they recommend different acts in Newcomb-style examples (broadly construed) where acts and states are correlated in peculiar ways. However, this paper presents a class of non-Newcombian examples that evidential decision theory cannot adequately model whereas causal decision theory can. Briefly, the examples involve situations where it is clearly best to perform an act that will not influence the desired outcome. On evidential (...)
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  7.  42
    (1 other version)Goals and the Informativeness of Prior Probabilities.Olav Benjamin Vassend - 2017 - Erkenntnis:1-24.
    I argue that information is a goal-relative concept for Bayesians. More precisely, I argue that how much information is provided by a piece of evidence depends on whether the goal is to learn the truth or to rank actions by their expected utility, and that different confirmation measures should therefore be used in different contexts. I then show how information measures may reasonably be derived from confirmation measures, and I show how to derive goal-relative non-informative and informative priors given background (...)
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  8.  44
    On the Ecological and Internal Rationality of Bayesian Conditionalization and Other Belief Updating Strategies.Olav Benjamin Vassend - forthcoming - British Journal for the Philosophy of Science.
  9.  30
    What hinge epistemology and Bayesian epistemology can learn from each other.Olav Benjamin Vassend - 2023 - Asian Journal of Philosophy 2 (2):1-21.
    Hinge epistemology and Bayesianism are two prominent approaches in contemporary epistemology, but the relationship between these approaches has not been systematically studied. This paper formalizes the central commitments of hinge epistemology in a Bayesian framework and argues for the following two theses: (1) many of the types of claims that are treated as paradigmatic hinges in the hinge epistemology literature, such as the claim that there exists an external world of physical objects, are not capable of enabling rational inquiry, even (...)
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  10.  36
    Review of Bayesian Philosophy of Science. [REVIEW]Olav Benjamin Vassend - 2023 - Erkenntnis 88 (5):2245-2249.
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