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

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.

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Journal
Proceedings of the ... International Florida Artificial Intelligence Research Society Conference
Published
2025-05-14
DOI
https://doi.org/10.32473/flairs.38.1.138854
Primary Topic
Logic, Reasoning, and Knowledge
Type
article
Field-Weighted Citation Impact
0.00

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article

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

Antje Claußnitzer, Franz Baader
Proceedings of the ... International Florida Artificial Intelligence Research Society Conference
Logic, Reasoning, and Knowledge
article

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

Antje Claußnitzer, Franz Baader
article en

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.

Proceedings of the ... International Florida Artificial Intelligence Research Society ConferenceVol. 38
Technische Universität Dresden (DE)
Bundesministerium für Bildung und Forschung, Sächsisches Staatsministerium für Wissenschaft und Kunst
Openalex Percentile: Top 70%
Logic, Reasoning, and Knowledge
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