Epistemic-entrenchment Characterization of Parikh’s Axiom

Authors: Theofanis Aravanis, Pavlos Peppas, Mary-Anne Williams

IJCAI 2017 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Theoretical In this article, we provide the epistemic-entrenchment characterization of the weak version of Parikh s relevance-sensitive axiom for belief revision known as axiom (P) for the general case of incomplete theories. The above-mentioned characterization, essentially, constitutes additional constraints on epistemic-entrenchment preorders, that induce AGM revision functions, satisfying the weak version of Parikh s axiom (P). Theorem 1 below establishes the connection between (Q1) (Q2) and (EP1) (EP2), and, thus, provides the epistemic-entrenchment characterization of the weak version of axiom (P), for the general case of incomplete theories.
Researcher Affiliation Academia Theofanis Aravanis1, Pavlos Peppas1,2, Mary-Anne Williams2 1University of Patras, Greece 2University of Technology Sydney, Australia {taravanis, pavlos}@upatras.gr, Mary-Anne.Williams@uts.edu.au
Pseudocode No The paper presents formal definitions, axioms, and a mathematical proof (Theorem 1), but it does not include any pseudocode or algorithm blocks.
Open Source Code No The paper is theoretical, focusing on mathematical characterization, and does not mention releasing any source code.
Open Datasets No The paper is a theoretical work on belief revision, focusing on mathematical characterization, and does not use or reference any datasets for training or evaluation.
Dataset Splits No The paper is theoretical and presents a mathematical characterization, therefore, it does not involve dataset validation or specific splits for training, validation, or testing.
Hardware Specification No The paper is theoretical, presenting a mathematical characterization and proof, and therefore does not discuss any hardware used for experiments.
Software Dependencies No The paper is theoretical and presents a formal characterization, not an implementation or empirical study, so it does not list any software dependencies with specific version numbers.
Experiment Setup No The paper is theoretical, providing a mathematical characterization and proof, and thus does not describe any experimental setup details or hyperparameters.