A Logical Framework Perspective on Conservativity

Rabe F (2024)


Publication Type: Conference contribution

Publication year: 2024

Journal

Publisher: Springer Science and Business Media Deutschland GmbH

Book Volume: 14960 LNAI

Pages Range: 203-219

Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Event location: Montreal, QC, CAN

ISBN: 9783031669965

DOI: 10.1007/978-3-031-66997-2_12

Abstract

Conservative extension is one of the most important concepts in formal logic, capturing the intuition when an extension does not substantially change the extended language or theory. Multiple non-equivalent definitions have emerged, including conceptually very different ones in proof and model theory. We use a logical framework that allows stating these notions in a logic-independent way. This allows proving several meta-theorems that yield new intuitions about conservativity: The existence of the different notions of conservativity is neither a coincidence nor a defect: we recover them as canonical points on a spectrum of gradual refinement from syntax to semantics. Moreover, the model and proof-theoretical notions correspond to the well-known difference between admissible and derivable rules. Finally, we can formally capture that the completeness of a logic corresponds to the conservativity of its semantics. All results are intuitively simple but have previously not been stated rigorously and in full generality.

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How to cite

APA:

Rabe, F. (2024). A Logical Framework Perspective on Conservativity. In Andrea Kohlhase, Laura Kovács (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 203-219). Montreal, QC, CAN: Springer Science and Business Media Deutschland GmbH.

MLA:

Rabe, Florian. "A Logical Framework Perspective on Conservativity." Proceedings of the 17th International Conference on Intelligent Computer Mathematics, CICM 2024, Montreal, QC, CAN Ed. Andrea Kohlhase, Laura Kovács, Springer Science and Business Media Deutschland GmbH, 2024. 203-219.

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