An application of variable-valued logic to inductive learning of plant disease diagnostic rules
MVL '76 Proceedings of the sixth international symposium on Multiple-valued logic
Control requirements for the design of production system architectures
Proceedings of the 1977 symposium on Artificial intelligence and programming languages
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An information processing model of some important aspects of inductive reasoning is presented within the context of one scientific discipline. Given a collection of experimental (mass spectrometry) data from several chemical molecules the computer program described here separates the molecules into "well-behaved" subclasses and selects from the space of all explanatory processes the "characteristic" processes for each subclass. The definitions of "well-behaved" and "characteristic" embody several heuristics which are discussed. Some results of the program are discussed which have been useful to chemists and which lend credibility to this approach.