Abstract
One of the major requirements of an expert system designed to be able to reason cogently with both certain and uncertain information is that it should demonstrably perform its reasoning task within a reasonable amount of time. However, various simplification strategies operated by early expert systems, do in the long run, lead to continued and sustained errors of judgement on the part of the reasoning process. So much so, that criticisms can be made against almost all of the present day methods for reasoning with uncertainty (Prade, 1983), (Stephanou and Sage 1987).
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Kane, T.B. (1991). Reasoning with Maximum Entropy in Expert Systems. In: Grandy, W.T., Schick, L.H. (eds) Maximum Entropy and Bayesian Methods. Fundamental Theories of Physics, vol 43. Springer, Dordrecht. https://doi.org/10.1007/978-94-011-3460-6_19
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DOI: https://doi.org/10.1007/978-94-011-3460-6_19
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