English

Modal reduction principles: a parametric shift to graphs

Logic 2024-03-22 v1

Abstract

Graph-based frames have been introduced as a logical framework which internalizes an inherent boundary to knowability. They also support the interpretation of lattice-based (modal) logics as hyper-constructive logics of evidential reasoning. Conceptually, the present paper proposes graph-based frames as a formal framework suitable for generalizing Pawlak's rough set theory to a setting in which inherent limits to knowability need to be considered. Technically, the present paper establishes systematic connections between the first-order correspondents of Sahlqvist modal reduction principles on Kripke frames, and on the more general relational environments of graph-based and polarity-based frames. This work is part of a research line aiming at: (a) comparing and inter-relating the various (first-order) conditions corresponding to a given (modal) axiom in different relational semantics (b) recognizing when first-order sentences in the frame-correspondence languages of different relational structures encode the same modal content (c) meaningfully transferring relational properties across different semantic contexts. The present paper develops these results for the graph-based semantics, polarity-based semantics, and all Sahlqvist modal reduction principles. As an application, we study well known modal axioms in rough set theory on graph-based frames and show that, although these axioms correspond to different first-order conditions on graph-based frames, their intuitive meaning is retained.This allows us to introduce the notion of hyperconstructivist approximation spaces as the subclass of graph-based frames defined by the first-order conditions corresponding to the same modal axioms defining classical generalized approximation spaces, and to transfer the properties and the intuitive understanding of different approximation spaces to graph-based frames.

Keywords

Cite

@article{arxiv.2403.14026,
  title  = {Modal reduction principles: a parametric shift to graphs},
  author = {Willem Conradie and Krishna Manoorkar and Alessandra Palmigiano and Mattia Panettiere},
  journal= {arXiv preprint arXiv:2403.14026},
  year   = {2024}
}
R2 v1 2026-06-28T15:28:04.832Z