Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Bayesian Networks and Decision Graphs
Bayesian Networks and Decision Graphs
Artificial Intelligence: A Guide to Intelligent Systems
Artificial Intelligence: A Guide to Intelligent Systems
An architecture for adaptive intelligent systems
Artificial Intelligence
Fuzzy Classifier Design
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The paper demonstrates briefly the reasoning capabilities in condition monitoring offered by systems based on statement networks. The usefulness of the networks considered results among others from possibilities of their optimization related to the minimization of contradictions between rules acquired from different knowledge sources. A mechanical analogy of such networks introduces an interpretation of statements as material points that are able to move. Dependencies between statements are considered as approximate necessary and approximate sufficient conditions, which are represented by unilateral constraints imposed on the introduced material points. A model of a dynamic statement network can be obtained out of the network consisting of statements represented by material points with assigned masses, where the inertia of statements may be taken into account. The paper introduces a measure of conditional contradictions of statements, which can be used for monitoring knowledge bases in running expert systems.