A logical Approach to Case-Based Reasoning Using Fuzzy Similarity Relations

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Authors:
Enric Plaza
Francesc Esteva
Pere Garcia
Lluís Godo
Ramon López de Mántaras
Title: A logical Approach to Case-Based Reasoning Using Fuzzy Similarity Relations
Journal: International Journal of Information Sciences
Volume 106
Number
Pages: 105-122
Year: 1998



Abstract

This article approaches the formalization of inference in Case-based Reasoning (CBR) systems. CBR systems infer solutions of new problems on the basis of a precedent case that is, to some extent, similar to the current problem. Using the logics developed for similarity-based inference we characterize CBR systems defining what we call the Precedent-based Plausible Reasoning (PPR) model. This model is based on the graded consequence relations named approximation entailment and proximity entailment. A modal interpretation is provided for the precedent-based inference where the plausibility is given by the graded possibility operator Failed to parse (MathML with SVG or PNG fallback (recommended for modern browsers and accessibility tools): Invalid response ("Math extension cannot connect to Restbase.") from server "https://api.formulasearchengine.com/v1/":): {\displaystyle \Diamond_\alpha} . The PPR model shows that both knowledge-intensive CBR systems and nearest neighbor algorithms share a common core formalism and that their difference is on whether (respectively) they use a general theory in addition to the precedent cases or they do not.