A Cognitively Inspired Approach for Knowledge Representation and Reasoning in Knowledge-Based Systems

In this thesis, I investigate a hybrid knowledge representation approach that combines classic knowledge representations, such as rules and ontologies, with other cognitively plausible representations, such as prototypes and exemplars. The resulting framework can combine the strengths of each approach of knowledge representation, avoiding their weaknesses. It can be used for developing knowledge-based systems that combine logicbased reasoning and similarity-based reasoning in problem-solving processes.