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Grundlagen der Wahrscheinlichkeitsrechnung

Springer: Berlin (1933)

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  1. Sleeping Beauty: Exploring a Neglected Solution.Laureano Luna - 2020 - British Journal for the Philosophy of Science 71 (3):1069-1092.
    The strong law of large numbers and considerations concerning additional information strongly suggest that Beauty upon awakening has probability 1/3 to be in a heads-awakening but should still believe the probability that the coin landed heads in the Sunday toss to be 1/2. The problem is that she is in a heads-awakening if and only if the coin landed heads. So, how can she rationally assign different probabilities or credences to propositions she knows imply each other? This is the problem (...)
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  • Philosophy as conceptual engineering: Inductive logic in Rudolf Carnap's scientific philosophy.Christopher F. French - 2015 - Dissertation, University of British Columbia
    My dissertation explores the ways in which Rudolf Carnap sought to make philosophy scientific by further developing recent interpretive efforts to explain Carnap’s mature philosophical work as a form of engineering. It does this by looking in detail at his philosophical practice in his most sustained mature project, his work on pure and applied inductive logic. I, first, specify the sort of engineering Carnap is engaged in as involving an engineering design problem and then draw out the complications of design (...)
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  • Bayesian Epistemology.Stephan Hartmann & Jan Sprenger - 2010 - In Sven Bernecker & Duncan Pritchard (eds.), The Routledge Companion to Epistemology. New York: Routledge. pp. 609-620.
    Bayesian epistemology addresses epistemological problems with the help of the mathematical theory of probability. It turns out that the probability calculus is especially suited to represent degrees of belief (credences) and to deal with questions of belief change, confirmation, evidence, justification, and coherence. Compared to the informal discussions in traditional epistemology, Bayesian epis- temology allows for a more precise and fine-grained analysis which takes the gradual aspects of these central epistemological notions into account. Bayesian epistemology therefore complements traditional epistemology; it (...)
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  • Non-Ideal Decision Theory.Sven Neth - 2023 - Dissertation, University of California, Berkeley
    My dissertation is about Bayesian rationality for non-ideal agents. I show how to derive subjective probabilities from preferences using much weaker rationality assumptions than other standard representation theorems. I argue that non-ideal agents might be uncertain about how they will update on new information and consider two consequences of this uncertainty: such agents should sometimes reject free information and make choices which, taken together, yield sure loss. The upshot is that Bayesian rationality for non-ideal agents makes very different normative demands (...)
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  • What we can learn from how trivalent conditionals avoid triviality.Daniel Lassiter - 2020 - Inquiry: An Interdisciplinary Journal of Philosophy 63 (9-10):1087-1114.
    ABSTRACT A trivalent theory of indicative conditionals automatically enforces Stalnaker's thesis – the equation between probabilities of conditionals and conditional probabilities. This result holds because the trivalent semantics requires, for principled reasons, a modification of the ratio definition of conditional probability in order to accommodate the possibility of undefinedness. I explain how this modification is motivated and how it allows the trivalent semantics to avoid a number of well-known triviality results, in the process clarifying why these results hold for many (...)
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