Towards decision making via expressive probabilistic ontologies

Erman Acar; Camilo Thorne; Heiner Stuckenschmidt

doi:10.1007/978-3-319-23114-3_4

Towards decision making via expressive probabilistic ontologies

Erman Acar^*, Camilo Thorne, Heiner Stuckenschmidt

^*Corresponding author for this work

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

Abstract

We propose a framework for automated multi-attribute deci- sion making, employing the probabilistic non-monotonic description log- ics proposed by Lukasiewicz in 2008. Using this framework, we can model artificial agents in decision-making situation, wherein background knowl- edge, available alternatives and weighted attributes are represented via probabilistic ontologies. It turns out that extending traditional utility theory with such description logics, enables us to model decision-making problems where probabilistic ignorance and default reasoning plays an important role. We provide several decision functions using the notions of expected utility and probability intervals, and study their properties.

Original language	English
Title of host publication	Algorithmic Decision Theory
Subtitle of host publication	4th International Conference, ADT 2015, Lexington, KY, USA, September 27-30, 2015, Proceedings
Editors	Toby Walsh
Publisher	Springer Verlag
Pages	52-68
Number of pages	17
ISBN (Electronic)	9783319231143
ISBN (Print)	9783319231136
DOIs	https://doi.org/10.1007/978-3-319-23114-3_4
Publication status	Published - 2015
Externally published	Yes
Event	4th International Conference on Algorithmic Decision Theory, ADT 2015 - Lexington, United States Duration: 27 Sept 2015 → 30 Sept 2015

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9346
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	4th International Conference on Algorithmic Decision Theory, ADT 2015
Country/Territory	United States
City	Lexington
Period	27/09/15 → 30/09/15

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10.1007/978-3-319-23114-3_4

http://www.mendeley.com/research/towards-decision-making-via-expressive-probabilistic-ontologies

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Acar, E., Thorne, C., & Stuckenschmidt, H. (2015). Towards decision making via expressive probabilistic ontologies. In T. Walsh (Ed.), Algorithmic Decision Theory: 4th International Conference, ADT 2015, Lexington, KY, USA, September 27-30, 2015, Proceedings (pp. 52-68). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9346). Springer Verlag. Advance online publication. https://doi.org/10.1007/978-3-319-23114-3_4

Acar, Erman ; Thorne, Camilo ; Stuckenschmidt, Heiner. / Towards decision making via expressive probabilistic ontologies. Algorithmic Decision Theory: 4th International Conference, ADT 2015, Lexington, KY, USA, September 27-30, 2015, Proceedings. editor / Toby Walsh. Springer Verlag, 2015. pp. 52-68 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "We propose a framework for automated multi-attribute deci- sion making, employing the probabilistic non-monotonic description log- ics proposed by Lukasiewicz in 2008. Using this framework, we can model artificial agents in decision-making situation, wherein background knowl- edge, available alternatives and weighted attributes are represented via probabilistic ontologies. It turns out that extending traditional utility theory with such description logics, enables us to model decision-making problems where probabilistic ignorance and default reasoning plays an important role. We provide several decision functions using the notions of expected utility and probability intervals, and study their properties.",

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Acar, E, Thorne, C & Stuckenschmidt, H 2015, Towards decision making via expressive probabilistic ontologies. in T Walsh (ed.), Algorithmic Decision Theory: 4th International Conference, ADT 2015, Lexington, KY, USA, September 27-30, 2015, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9346, Springer Verlag, pp. 52-68, 4th International Conference on Algorithmic Decision Theory, ADT 2015, Lexington, United States, 27/09/15. https://doi.org/10.1007/978-3-319-23114-3_4

Towards decision making via expressive probabilistic ontologies. / Acar, Erman; Thorne, Camilo; Stuckenschmidt, Heiner.
Algorithmic Decision Theory: 4th International Conference, ADT 2015, Lexington, KY, USA, September 27-30, 2015, Proceedings. ed. / Toby Walsh. Springer Verlag, 2015. p. 52-68 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9346).

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

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AB - We propose a framework for automated multi-attribute deci- sion making, employing the probabilistic non-monotonic description log- ics proposed by Lukasiewicz in 2008. Using this framework, we can model artificial agents in decision-making situation, wherein background knowl- edge, available alternatives and weighted attributes are represented via probabilistic ontologies. It turns out that extending traditional utility theory with such description logics, enables us to model decision-making problems where probabilistic ignorance and default reasoning plays an important role. We provide several decision functions using the notions of expected utility and probability intervals, and study their properties.

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Acar E, Thorne C, Stuckenschmidt H. Towards decision making via expressive probabilistic ontologies. In Walsh T, editor, Algorithmic Decision Theory: 4th International Conference, ADT 2015, Lexington, KY, USA, September 27-30, 2015, Proceedings. Springer Verlag. 2015. p. 52-68. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). Epub 2015 Aug 28. doi: 10.1007/978-3-319-23114-3_4

Towards decision making via expressive probabilistic ontologies

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