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    Automated Reasoning with Analytic Tableaux and Related Methods

    32nd International Conference, TABLEAUX 2023, Prague, Czech Republic, September 18–21, 2023, Proceedings

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    Contributor(s)
    Ramanayake, Revantha (editor)
    Urban, Josef (editor)
    Language
    English
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    Abstract
    This open access book constitutes the proceedings of the proceedings of the 32nd International Conference on Automated Reasoning with Analytic Tableaux and Related Methods, TABLEAUX 2023, held in Prague, Czech Republic, during September 18-21, 2023. The 20 full papers and 5 short papers included in this book together with 5 abstracts of invited talks were carefully reviewed and selected from 43 submissions. They present research on all aspects of the mechanization of reasoning with tableaux and related methods. The papers are organized in the following topical sections: tableau calculi; sequent calculi; theorem proving; non-wellfounded proofs; modal logics; linear logic and MV-algebras; separation logic; and first-order logics.
    URI
    https://library.oapen.org/handle/20.500.12657/76757
    Keywords
    tableaux; tableaux calculus; sequent calculus; proof theory; theorem proving; proof assistant; natural deduction; formalized proof; decision procedures; automated deduction; SMT; resolution; cut-elimination; non-classical logics; modal logic; intuitionistic; inear logic; substructural logic; separation logic
    DOI
    10.1007/978-3-031-43513-3
    ISBN
    9783031435133, 9783031435126, 9783031435133
    Publisher
    Springer Nature
    Publisher website
    https://www.springernature.com/gp/products/books
    Publication date and place
    Cham, 2023
    Imprint
    Springer Nature Switzerland
    Series
    Lecture Notes in Computer Science; Lecture Notes in Artificial Intelligence, 14278
    Pages
    482
    Rights
    http://creativecommons.org/licenses/by/4.0/
    • Imported or submitted locally

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    License

    • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

    Credits

    • logo EU
    • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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