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A pseudo‐neural system for hypothesis selection

The article describes a system for hypothesis elicitation and ranking formed by a net of computational elements obtained by modifying the classical neural model of Caianiello. This neural structure was chosen on the basis both of knowledge representation and of parallel processing considerations. the two fundamental components of the system are an elaboration layer and, in case the available evidences are insufficient to trigger explanatory hypotheses, a query layer that enables the system to gather additional information. Algorithms that help setting the crucial variable parameters of the net are described in the Appendix. © 1992 John Wiley & Sons, Inc.