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Fragmentation and logical omniscience

Noûs 56 (3):716-741 (2022)

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  1. A Metalinguistic and Computational Approach to the Problem of Mathematical Omniscience.Zeynep Soysal - forthcoming - Philosophy and Phenomenological Research.
    Philosophy and Phenomenological Research, EarlyView.
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  • The Logic of Hyperlogic. Part A: Foundations.Alexander W. Kocurek - forthcoming - Review of Symbolic Logic:1-27.
    Hyperlogic is a hyperintensional system designed to regiment metalogical claims (e.g., "Intuitionistic logic is correct" or "The law of excluded middle holds") into the object language, including within embedded environments such as attitude reports and counterfactuals. This paper is the first of a two-part series exploring the logic of hyperlogic. This part presents a minimal logic of hyperlogic and proves its completeness. It consists of two interdefined axiomatic systems: one for classical consequence (truth preservation under a classical interpretation of the (...)
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  • Questions in Action.Daniel Hoek - 2022 - Journal of Philosophy 119 (3):113-143.
    Choices confront us with questions. How we act depends on our answers to those questions. So the way our beliefs guide our choices is not just a function of their informational content, but also depends systematically on the questions those beliefs address. This paper gives a precise account of the interplay between choices, questions and beliefs, and harnesses this account to obtain a principled approach to the problem of deduction. The result is a novel theory of belief-guided action that explains (...)
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  • Doubt.Luis Rosa - forthcoming - In Kurt Sylvan (ed.), The Blackwell Companion to Epistemology, Third Edition.
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  • Rational Polarization.Kevin Dorst - manuscript
    Predictable polarization is everywhere: we can often predict how people’s opinions—including our own—will shift over time. Extant theories either neglect the fact that we can predict our own polarization, or explain it through irrational mechanisms. We needn’t. Empirical studies suggest that polarization is predictable when evidence is ambiguous, i.e. when the rational response is not obvious. I show how Bayesians should model such ambiguity, and then prove that—assuming rational updates are those which obey the value of evidence (Blackwell 1953; Good (...)
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