Abstract
In several subfields of Artificial Intelligence (AI) and in Discrete Event Modeling (DEM) there is a need to represent temporal and causal relationships in a problem domain. Some of these formalisms of AI and DEM are presented and compared. Most of the AI formalisms are beset by the frame, qualification, and/or ramification problems. DEM formalisms which can be viewed as formalisms for temporal and causal reasoning are not beset by these problems. They, however, in general, lack a formal theory. The Propositional Discrete Event Logic L PDE which avoids the characteristic problems of AI formalisms and which also gives a formal theory to DEM is briefly discussed. Examples illustrating the use of this logic are given.
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© 1990 Springer-Verlag Berlin Heidelberg
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Radiya, A., Sargent, R.G. (1990). Differing perspectives of knowledge representation in artificial intelligence and discrete event modeling. In: Ramani, S., Chandrasekar, R., Anjaneyulu, K.S.R. (eds) Knowledge Based Computer Systems. KBCS 1989. Lecture Notes in Computer Science, vol 444. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0018380
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DOI: https://doi.org/10.1007/BFb0018380
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