Abstract

Typical examples, that is, examples that are representative for a particular situation or concept, play an important role in human knowledge representation and reasoning. In real life situations more often than not, instead of a lengthy abstract characterization, a typical example is used to describe the situation. This well-known observation has been the motivation for various investigations in experimental psychology, which also motivate our formal characterization of typical examples, based on a partial order for their typicality. Reasoning by typical examples is then developed as a special case of analogical reasoning using the semantic information contained in the corresponding concept structures. We derive new inference rules by replacing the explicit information about connections and similarity, which are normally used to formalize analogical inference rules, by information about the relationship to typical examples. Using these inference rules analogical reasoning proceeds by c...

Keywords:
Computer science Inference Analogical reasoning Knowledge representation and reasoning Artificial intelligence Representation (politics) Similarity (geometry) Model-based reasoning Automated reasoning Reasoning system Non-monotonic logic Deductive reasoning Natural language processing Analogy Epistemology

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Citation History

Topics

Semantic Web and Ontologies
Physical Sciences →  Computer Science →  Artificial Intelligence
Logic, Reasoning, and Knowledge
Physical Sciences →  Computer Science →  Artificial Intelligence
Constraint Satisfaction and Optimization
Physical Sciences →  Computer Science →  Computer Networks and Communications

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