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  1. Updating incoherent credences ‐ Extending the Dutch strategy argument for conditionalization.Glauber De Bona & Julia Staffel - 2021 - Philosophy and Phenomenological Research 105 (2):435-460.
    In this paper, we ask: how should an agent who has incoherent credences update when they learn new evidence? The standard Bayesian answer for coherent agents is that they should conditionalize; however, this updating rule is not defined for incoherent starting credences. We show how one of the main arguments for conditionalization, the Dutch strategy argument, can be extended to devise a target property for updating plans that can apply to them regardless of whether the agent starts out with coherent (...)
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  • Deciding Koopman's qualitative probability.Daniele Mundici - 2021 - Artificial Intelligence 299 (C):103524.
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  • How do Beliefs Simplify Reasoning?Julia Staffel - 2019 - Noûs 53 (4):937-962.
    According to an increasingly popular epistemological view, people need outright beliefs in addition to credences to simplify their reasoning. Outright beliefs simplify reasoning by allowing thinkers to ignore small error probabilities. What is outright believed can change between contexts. It has been claimed that thinkers manage shifts in their outright beliefs and credences across contexts by an updating procedure resembling conditionalization, which I call pseudo-conditionalization (PC). But conditionalization is notoriously complicated. The claim that thinkers manage their beliefs via PC is (...)
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  • Should I pretend I'm perfect?Julia Staffel - 2017 - Res Philosophica 94 (2):301-324.
    Ideal agents are role models whose perfection in some normative domain we try to approximate. But which form should this striving take? It is well known that following ideal rules of practical reasoning can have disastrous results for non-ideal agents. Yet, this issue has not been explored with respect to rules of theoretical reasoning. I show how we can extend Bayesian models of ideally rational agents in order to pose and answer the question of whether non-ideal agents should form new (...)
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  • Localising iceberg inconsistencies.Glauber De Bona & Anthony Hunter - 2017 - Artificial Intelligence 246 (C):118-151.
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  • Why be coherent?Glauber De Bona & Julia Staffel - 2018 - Analysis 78 (3):405-415.
    Bayesians defend norms of ideal rationality such as probabilism, which they claim should be approximated by non-ideal thinkers. Yet, it is not often discussed exactly in what sense it is beneficial for an agent’s credence function to approximate probabilistic coherence. Some existing research indicates that approximating coherence leads to improvements in accuracy, whereas other research suggests that it decreases Dutch book vulnerability. Yet, the existing results don’t settle whether there is a way of approximating coherence that delivers both benefits at (...)
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  • Syntactic reasoning with conditional probabilities in deductive argumentation.Anthony Hunter & Nico Potyka - 2023 - Artificial Intelligence 321 (C):103934.
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  • On measuring inconsistency in definite and indefinite databases with denial constraints.Francesco Parisi & John Grant - 2023 - Artificial Intelligence 318 (C):103884.
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  • Graded Incoherence for Accuracy-Firsters.Glauber De Bona & Julia Staffel - 2017 - Philosophy of Science 84 (2):189-213.
    This paper investigates the relationship between two evaluative claims about agents’ de- grees of belief: (i) that it is better to have more, rather than less accurate degrees of belief, and (ii) that it is better to have less, rather than more probabilistically incoherent degrees of belief. We show that, for suitable combinations of inaccuracy measures and incoherence measures, both claims are compatible, although not equivalent; moreover, certain ways of becoming less incoherent always guarantee improvements in accuracy. Incompatibilities between particular (...)
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  • Handling and measuring inconsistency in non-monotonic logics.Markus Ulbricht, Matthias Thimm & Gerhard Brewka - 2020 - Artificial Intelligence 286 (C):103344.
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  • Advanced modalizing de dicto and de re.John Divers & John J. Parry - 2018 - Analysis 78 (3):415-425.
    Lewis’ analysis of modality faces a problem in that it appears to confer unintended truth values to certain modal claims about the pluriverse: e.g. ‘It is possible that there are many worlds’ is false when we expect truth. This is the problem of advanced modalizing. Divers presents a principled solution to this problem by treating modal modifiers as semantically redundant in some such cases. However, this semantic move does not deal adequately with advanced de re modal claims. Here, we motivate (...)
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  • On measuring inconsistency in graph databases with regular path constraints.John Grant & Francesco Parisi - 2024 - Artificial Intelligence 335 (C):104197.
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  • Probabilistic Entailment on First Order Languages and Reasoning with Inconsistencies.R. A. D. Soroush Rafiee - 2023 - Review of Symbolic Logic 16 (2):351-368.
    We investigate an approach for drawing logical inference from inconsistent premisses. The main idea in this approach is that the inconsistencies in the premisses should be interpreted as uncertainty of the information. We propose a mechanism, based on Kinght’s [14] study of inconsistency, for revising an inconsistent set of premisses to a minimally uncertain, probabilistically consistent one. We will then generalise the probabilistic entailment relation introduced in [15] for propositional languages to the first order case to draw logical inference from (...)
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  • On the complexity of inconsistency measurement.Matthias Thimm & Johannes P. Wallner - 2019 - Artificial Intelligence 275 (C):411-456.
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