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29 March 1988 A Logic-Based Prototyping Environment For Process Oriented Second Generation Expert Systems
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Abstract
Logic programming methods have been used to implement an expert system shell which represents and reasons about the implications of causal event streams, in arbitrarily complex causal networks. The system features the capability of "forward" and "backward" inference, "fuzzy" causal inference, default vs conditional reasoning, the ability to combine 1st generation "if-then" heuristics with 2nd generation structural inference during fault diagnosis exercises and the ability to generate inferences from empirical data as well as from conceptually based models of causal relationships. A description of the direct causal connections between pairs of focal events (the causal topology), along with the enumeration of policy variables (manipulable inputs), system observables (events which can be observed) and goal variables (desired outputs) enable declarative representations of meta-level causal structures used during the causal inference process. The simplicity of these input requirements, the expressive power of an open ended Logic Programming environment and the availability of a rich set of analytic tools all combine to provide the knowledge engineer with the ability to quickly build systems which can reason symbolically about complex causal structures.
© (1988) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Edward H. Freeman "A Logic-Based Prototyping Environment For Process Oriented Second Generation Expert Systems", Proc. SPIE 0937, Applications of Artificial Intelligence VI, (29 March 1988); https://doi.org/10.1117/12.946966
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