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  1. (1 other version)Do We Need Second‐Order Probabilities?Sven Ove Hansson - 2008 - Dialectica 62 (4):525-533.
    Although it has often been claimed that all the information contained in second‐order probabilities can be contained in first‐order probabilities, no practical recipe for the elimination of second‐order probabilities without loss of information seems to have been presented. Here, such an elimination method is introduced for repeatable events. However, its application comes at the price of losses in cognitive realism. In spite of their technical eliminability, second‐order probabilities are useful because they can provide models of important features of the world (...)
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  • Deliberation and confidence change.Nora Heinzelmann & Stephan Hartmann - 2022 - Synthese 200 (1):1-13.
    We argue that social deliberation may increase an agent’s confidence and credence under certain circumstances. An agent considers a proposition H and assigns a probability to it. However, she is not fully confident that she herself is reliable in this assignment. She then endorses H during deliberation with another person, expecting him to raise serious objections. To her surprise, however, the other person does not raise any objections to H. How should her attitudes toward H change? It seems plausible that (...)
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  • Bayesian Belief Revision Based on Agent’s Criteria.Yongfeng Yuan - 2021 - Studia Logica 109 (6):1311-1346.
    In the literature of belief revision, it is widely accepted that: there is only one revision phase in belief revision which is well characterized by the Bayes’ Rule, Jeffrey’s Rule, etc.. However, as I argue in this article, there are at least four successive phases in belief revision, namely first/second order evaluation and first/second order revision. To characterize these phases, I propose mainly four rules of belief revision based on agent’s criteria, and make one composition rule to characterize belief revision (...)
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  • Measuring Uncertainty.Sven Ove Hansson - 2009 - Studia Logica 93 (1):21-40.
    Two types of measures of probabilistic uncertainty are introduced and investigated. Dispersion measures report how diffused the agent’s second-order probability distribution is over the range of first-order probabilities. Robustness measures reflect the extent to which the agent’s assessment of the prior (objective) probability of an event is perturbed by information about whether or not the event actually took place. The properties of both types of measures are investigated. The most obvious type of robustness measure is shown to coincide with one (...)
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  • (1 other version)Do we need second-order probabilities?Sven Ove Hansson - 2008 - Dialectica 62 (4):525-533.
    Although it has often been claimed that all the information contained in second-order probabilities can be contained in first-order probabilities, no practical recipe for the elimination of second-order probabilities without loss of information seems to have been presented. Here, such an elimination method is introduced for repeatable events. However, its application comes at the price of losses in cognitive realism. In spite of their technical eliminability, second-order probabilities are useful because they can provide models of important features of the world (...)
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  • A Challenge to the Compound Lottery Axiom: A Two-Stage Normative Structure and Comparison to Other Theories.Donald B. Davis - 1994 - Theory and Decision 37 (3):267.
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  • On the Rationality of Decisions with Unreliable Probabilities.Birman Fernando - 2009 - Disputatio 3 (26):97-116.
    The standard Bayesian recipe for selecting the rational choice is presented. A familiar example in which the recipe fails to produce any definite result is introduced. It is argued that a generalization of Gärdenfors’ and Sahlin’s theory of unreliable probabilities — which itself does not guarantee a solution to the problem — offers the best available approach. But a number of challenges to this approach are also presented and discussed.
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