Work

Maximum Entropy Reasoning via Model Counting in (Description) Logics that Count

Year: 2025

Type: conference-paper

Abstract: In previous work it was shown that the logic ALCME, which extends the description logic (DL) ALC with probabilistic conditionals, has domain-lifted inference. Here, we extend this result from the base logic ALC to two logics that can count, the two-variable fragment C2 of first-order logic (FOL) with counting quantifiers, and the DL ALCSCC, which is not a fragment of FOL. As an auxiliary result, we prove that model counting in ALCSCC can be realized in a domain-liftable way.

Source: Proceedings of the ... International Florida Artificial Intelligence Research Society Conference

DOI: 10.32473/flairs.38.1.138854

Authors: Franz Baader, Anton Claußnitzer

Institution: Technische Universität Dresden

Language: English

Topic: Logic, Reasoning, and Knowledge

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: diamond

Funders: Bundesministerium für Bildung und Forschung, Sächsisches Staatsministerium für Wissenschaft und Kunst

Award: G7668369193