Book chapter
A Case-Based Approach to Mutual Adaptation of Taxonomic Ontologies
Case-Based Reasoning Research and Development, pp 226-240
2012
Abstract
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).
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1 citations in Scopus
Details
- Title
- A Case-Based Approach to Mutual Adaptation of Taxonomic Ontologies
- Creators
- Sergio Manzano - Artificial Intelligence Research InstituteSantiago Ontañón - Drexel UniversityEnric Plaza - Artificial Intelligence Research Institute
- Publication Details
- Case-Based Reasoning Research and Development, pp 226-240
- Series
- Lecture Notes in Computer Science
- Publisher
- Springer Berlin Heidelberg; Berlin, Heidelberg
- Resource Type
- Book chapter
- Language
- English
- Academic Unit
- Computer Science (Computing)
- Scopus ID
- 2-s2.0-84866644501
- Other Identifier
- 991021869011404721