Probabilistic Description Logics for Subjective Uncertainty
Gutierrez-Basulto, Victor, Jung, Jean Christoph, Lutz, Carsten, Schröder, Lutz
–Journal of Artificial Intelligence Research
We propose a family of probabilistic description logics (DLs) that are derived in a principled way from Halpern's probabilistic first-order logic. The resulting probabilistic DLs have a two-dimensional semantics similar to temporal DLs and are well-suited for representing subjective probabilities. We carry out a detailed study of reasoning in the new family of logics, concentrating on probabilistic extensions of the DLs ALC and EL, and showing that the complexity ranges from PTime via ExpTime and 2ExpTime to undecidable.
Journal of Artificial Intelligence Research
Jan-10-2017
- Country:
- Europe
- United Kingdom > England
- Cambridgeshire > Cambridge (0.04)
- Germany
- Bremen > Bremen (0.28)
- Bavaria > Middle Franconia
- Nuremberg (0.04)
- United Kingdom > England
- Europe
- Industry:
- Health & Medicine > Therapeutic Area (0.68)
- Technology:
- Information Technology > Artificial Intelligence > Representation & Reasoning
- Uncertainty (1.00)
- Ontologies (1.00)
- Logic & Formal Reasoning (1.00)
- Description Logic (1.00)
- Information Technology > Artificial Intelligence > Representation & Reasoning