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Epistemic Logic and Epistemology

In Sven Ove Hansson Vincent F. Hendricks (ed.), Handbook of Formal Philosophy. Springer. pp. 351-369 (2018)

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  1. Information dynamics and uniform substitution.Wesley H. Holliday, Tomohiro Hoshi & Thomas F. Icard Iii - 2013 - Synthese 190 (1):31-55.
    The picture of information acquisition as the elimination of possibilities has proven fruitful in many domains, serving as a foundation for formal models in philosophy, linguistics, computer science, and economics. While the picture appears simple, its formalization in dynamic epistemic logic reveals subtleties: given a valid principle of information dynamics in the language of dynamic epistemic logic, substituting complex epistemic sentences for its atomic sentences may result in an invalid principle. In this article, we explore such failures of uniform substitution. (...)
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  • Epistemic Closure and Epistemic Logic I: Relevant Alternatives and Subjunctivism.Wesley H. Holliday - 2015 - Journal of Philosophical Logic 44 (1):1-62.
    Epistemic closure has been a central issue in epistemology over the last forty years. According to versions of the relevant alternatives and subjunctivist theories of knowledge, epistemic closure can fail: an agent who knows some propositions can fail to know a logical consequence of those propositions, even if the agent explicitly believes the consequence (having “competently deduced” it from the known propositions). In this sense, the claim that epistemic closure can fail must be distinguished from the fact that agents do (...)
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  • Index, context, and the content of knowledge.Brian Rabern - 2017 - In Jonathan Jenkins Ichikawa (ed.), The Routledge Handbook of Epistemic Contextualism. Routledge. pp. 465-479.
    The verb 'knows' is often taken to be context-sensitive in an interesting way. What 'knows' means seems to be sensitive to the epistemic features of the context, e.g. the epistemic standard in play, the set of relevant alternatives, etc. There are standard model-theoretic semantic frameworks which deal with both intensional operators and context-sensitive expressions. In this chapter, we provide a brief overview of the various moving parts of these frameworks, the roles of context and index, the need for double indexing, (...)
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  • Two Reformulations of the Verificationist Thesis in Epistemic Temporal Logic that Avoid Fitch’s Paradox.Alexandru Dragomir - 2014 - Romanian Journal of Analytic Philosophy 8 (1):44-62.
    1) We will begin by offering a short introduction to Epistemic Logic and presenting Fitch’s paradox in an epistemic‑modal logic. (2) Then, we will proceed to presenting three Epistemic Temporal logical frameworks creat‑ ed by Hoshi (2009) : TPAL (Temporal Public Announcement Logic), TAPAL (Temporal Arbitrary Public Announcement Logic) and TPAL+P ! (Temporal Public Announcement Logic with Labeled Past Operators). We will show how Hoshi stated the Verificationist Thesis in the language of TAPAL and analyze his argument on why this (...)
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  • Does Amy know Ben knows you know your cards? A computational model of higher-order epistemic reasoning.Cedegao Zhang, Huang Ham & Wesley H. Holliday - 2021 - Proceedings of CogSci 2021.
    Reasoning about what other people know is an important cognitive ability, known as epistemic reasoning, which has fascinated psychologists, economists, and logicians. In this paper, we propose a computational model of humans’ epistemic reasoning, including higher-order epistemic reasoning—reasoning about what one person knows about another person’s knowledge—that we test in an experiment using a deductive card game called “Aces and Eights”. Our starting point is the model of perfect higher-order epistemic reasoners given by the framework of dynamic epistemic logic. We (...)
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  • A Computational Learning Semantics for Inductive Empirical Knowledge.Kevin T. Kelly - 2014 - In Alexandru Baltag & Sonja Smets (eds.), Johan van Benthem on Logic and Information Dynamics. Springer International Publishing. pp. 289-337.
    This chapter presents a new semantics for inductive empirical knowledge. The epistemic agent is represented concretely as a learner who processes new inputs through time and who forms new beliefs from those inputs by means of a concrete, computable learning program. The agent’s belief state is represented hyper-intensionally as a set of time-indexed sentences. Knowledge is interpreted as avoidance of error in the limit and as having converged to true belief from the present time onward. Familiar topics are re-examined within (...)
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