Abstract
This paper proposes a probabilistic extension for the semantics of hybrid represen- tation systems comprising both a terminological and an assertional component. This extension maintains the original performance of drawing inferences on a hierarchy of terminological defi- nitions. It enlarges its range of applicability to real world environments determined not only by definitional but also by uncertain knowledge.
On the basis of the language construct “probabilistic implication” it is shown how belief and em- pirical information on concept dependencies can be represented. The concept of “probabilistic inheritance” is introduced. This also applies to inheritance problems like exception handling and multiple inheritance under “conflicting” information. Further, it is shown how simple inferences can be drawn using terminological, probabilistic, and assertional knowledge.
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Heinsohn, J., Owsnicki-Klewe, B. (1988). Probabilistic Inheritance and Reasoning in Hybrid Knowledge Representation Systems. In: Hoeppner, W. (eds) Künstliche Intelligenz. Informatik-Fachberichte, vol 181. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-74064-0_5
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DOI: https://doi.org/10.1007/978-3-642-74064-0_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-50293-7
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