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AAAI 2007

Complexity Boundaries for Horn Description Logics

Conference Paper Knowledge Representation and Logic Artificial Intelligence

Abstract

Horn description logics (Horn-DLs) have recently started to attract attention due to the fact that their (worst-case) data complexities are in general lower than their overall (i. e. combined) complexities, which makes them attractive for reasoning with large ABoxes. However, the natural question whether Horn-DLs also provide advantages for TBox reasoning has hardly been addressed so far. In this paper, we therefore provide a thorough and comprehensive analysis of the combined complexities of Horn-DLs. While the combined complexity for many Horn-DLs turns out to be the same as for their non-Horn counterparts, we identify subboolean DLs where Hornness simplifies reasoning.

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Context

Venue
AAAI Conference on Artificial Intelligence
Archive span
1980-2026
Indexed papers
28718
Paper id
310395163315296781
v2026.09.13