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{{Publikation Erster Autor
{{Publikation Erster Autor
|ErsterAutorVorname=Ismail Ilkan
|ErsterAutorVorname=İsmail İlkan
|ErsterAutorNachname=Ceylan
|ErsterAutorNachname=Ceylan
|FurtherAuthors=Rafael Peñaloza
|FurtherAuthors=Rafael Peñaloza
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|Referiert=1
|Referiert=1
|Title=The Bayesian Description Logic BEL
|Title=The Bayesian Description Logic BEL
|To appear=0
|Year=2014
|Year=2014
|Month=
|Booktitle=Proceedings of the 7th International Joint Conference on Automated Reasoning (IJCAR 2014)
|Booktitle=Proceedings of the 7th International Joint Conference on Automated Reasoning (IJCAR 2014)
|Editor=Stephane Demri and Deepak Kapur and Christoph Weidenbach
|Note=
|Organization=
|Pages=480-494
|Pages=480-494
|Publisher=Springer
|Publisher=Springer
|Editor=Stephane Demri and Deepak Kapur and Christoph Weidenbach
|Series=Lecture Notes in Computer Science
|Series=Lecture Notes in Computer Science
|Volume=8562
|Volume=8562
|To appear=0
|Organization=
}}
}}
{{Publikation Details
{{Publikation Details
|Abstract=We introduce the probabilistic Description Logic BEL. In BEL, axioms are required to hold only in an associated context. The probabilistic component of the logic is given by a Bayesian network that describes the joint probability distribution of the contexts. We study the main reasoning problems in this logic; in particular, we (i) prove that deciding positive and almost-sure entailments is not harder for BEL than for the BN, and (ii) show how to compute the probability, and the most likely context for a consequence.
|Abstract=We introduce the probabilistic Description Logic BEL. In BEL, axioms are required to hold only in an associated context. The probabilistic component of the logic is given by a Bayesian network that describes the joint probability distribution of the contexts. We study the main reasoning problems in this logic; in particular, we (i) prove that deciding positive and almost-sure entailments is not harder for BEL than for the BN, and (ii) show how to compute the probability, and the most likely context for a consequence.
|ISBN=
|ISSN=
|Link=
|Download=CePe-IJCAR14.pdf
|Download=CePe-IJCAR14.pdf
|Slides=
|DOI Name=
|Projekt=
|Forschungsgruppe=Automatentheorie
|Forschungsgruppe=Automatentheorie
|BibTex=@inproceedings{ CePe-IJCAR14,
  author = {Ismail Ilkan {Ceylan} and Rafael {Pe{\~n}aloza} },
  booktitle = {Proceedings of the 7th International Joint Conference on Automated Reasoning (IJCAR 2014)},
  editor = {Stephane {Demri} and Deepak {Kapur} and Christoph {Weidenbach} },
  pages = {480--494},
  publisher = {Springer},
  series = {Lecture Notes in Computer Science},
  title = {The Bayesian Description Logic BEL},
  volume = {8562},
  year = {2014},
}
}}
}}

Aktuelle Version vom 19. Juni 2015, 16:35 Uhr

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İsmail İlkan Ceylan, Rafael Peñaloza
The Bayesian Description Logic BEL
In Stephane Demri and Deepak Kapur and Christoph Weidenbach, eds., Proceedings of the 7th International Joint Conference on Automated Reasoning (IJCAR 2014), volume 8562 of Lecture Notes in Computer Science, 480-494, 2014. Springer
  • KurzfassungAbstract
    We introduce the probabilistic Description Logic BEL. In BEL, axioms are required to hold only in an associated context. The probabilistic component of the logic is given by a Bayesian network that describes the joint probability distribution of the contexts. We study the main reasoning problems in this logic; in particular, we (i) prove that deciding positive and almost-sure entailments is not harder for BEL than for the BN, and (ii) show how to compute the probability, and the most likely context for a consequence.
  • Forschungsgruppe:Research Group: AutomatentheorieAutomata Theory
The final publication is available at Springer.
@inproceedings{CP2014,
  author    = {{\.{I}}smail {\.{I}}lkan Ceylan and Rafael Pe{\~{n}}aloza},
  title     = {The Bayesian Description Logic {BEL}},
  editor    = {Stephane Demri and Deepak Kapur and Christoph Weidenbach},
  booktitle = {Proceedings of the 7th International Joint Conference on
               Automated Reasoning (IJCAR 2014)},
  series    = {Lecture Notes in Computer Science},
  volume    = {8562},
  publisher = {Springer},
  year      = {2014},
  pages     = {480-494}
}