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Justification Awareness Models

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Logical Foundations of Computer Science (LFCS 2018)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10703))

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Abstract

Justification Awareness Models, JAMs, incorporate two principal ideas: (i) justifications are prime objects of the model: knowledge and belief are defined evidence-based concepts; (ii) awareness restrictions are applied to justifications rather than to propositions, which allows for the maintaining of desirable closure properties. JAMs naturally include major justification models, Kripke models and, in addition, represent situations with multiple possibly fallible justifications. As an example, we build a JAM for Russell’s well-known Prime Minister scenario which, in full generality, was previously off the scope of rigorous epistemic modeling.

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Notes

  1. 1.

    From [6]: “Hyperintensional contexts are simply contexts which do not respect logical equivalence”.

  2. 2.

    Which was true in 1912.

  3. 3.

    Moreover, one can easily imagine knowledge-producing reasoning from a source with false beliefs (both an atheist and a religious scientist can produce reliable knowledge products though one of them has false beliefs), so “false premises” are neither necessary nor sufficient for a justification to fail.

  4. 4.

    Which the author saw on the door of the Mathematics Support Center at Cornell in 2017.

  5. 5.

    In principle, one could consider smaller sets \(\mathcal A\), which would correspond to the high level of skepticism of an agent who does not necessarily accept logical truths (axioms) as justified. We leave this possibility for further studies.

  6. 6.

    In which we suppress the knowledge-producing component \(\mathcal{E}\) to capture beliefs.

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Acknowledgements

The author is grateful to Melvin Fitting, Vladimir Krupski, Elena Nogina, and Tudor Protopopescu for helpful suggestions. Special thanks to Karen Kletter for editing and proofreading this text.

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Authors and Affiliations

  1. The City University of New York, The Graduate Center, 365 Fifth Avenue, New York City, NY, 10016, USA

    Sergei Artemov

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  1. Sergei Artemov
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Correspondence to Sergei Artemov .

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Editors and Affiliations

  1. City University of New York, New York, New York, USA

    Sergei Artemov

  2. Cornell University, Ithaca, New York, USA

    Anil Nerode

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Artemov, S. (2018). Justification Awareness Models. In: Artemov, S., Nerode, A. (eds) Logical Foundations of Computer Science. LFCS 2018. Lecture Notes in Computer Science(), vol 10703. Springer, Cham. https://doi.org/10.1007/978-3-319-72056-2_2

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  • DOI: https://doi.org/10.1007/978-3-319-72056-2_2

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