Towards decision making via expressive probabilistic ontologies (ADT 2015)

Erman Acar, Camilo Thorne, Heiner Stuckenschmidt

Research output: Contribution to ConferencePaperAcademic

Abstract

© Springer International Publishing Switzerland 2015. 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 languageEnglish
Pages52-68
Number of pages17
DOIs
Publication statusPublished - 2015

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Ontology
Decision making

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Towards decision making via expressive probabilistic ontologies (ADT 2015). / Acar, Erman; Thorne, Camilo; Stuckenschmidt, Heiner.

2015. 52-68.

Research output: Contribution to ConferencePaperAcademic

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