A Case-Based Approach to Mutual Adaptation of Taxonomic Ontologies

We present a general framework for addressing the problem of semantic intelligibility among artificial agents based on concepts integral to the case-based reasoning research program. For this purpose, we define case-based semiotics (CBS) (based on the well known notion of the semiotic triangle) as the model that defines semantic intelligibility. We show how traditional CBR notions like transformational adaptation can be used in the problem of two agents achieving mutual intelligibility over a collection of concepts (defined in CBS).