Ontology Architecture of a Neuro-psychoanalytical, Computational Model

Abstract

The paper introduces the ontological knowledge architecture of the psychoanalytical, hierarchical and computational model ARS (Artificial Recognition System). The ontology architecture of the model is represented by a knowledge base. Semantic and individual memories are realized by means of an ontological architecture. These memories are modeled in a triple notation by the knowledge representation languages Resource Description Framework (RDF) and Resource Description Framework Schema (RDFS). Additionally, rules are employed for reasoning in the semantic knowledge base (manipulation rules) and individual knowledge base (action rules). The approach uses RDF and RDFS for the representation of metadata describing the semantic and individual memories. The simulation shows that general concepts are needed to form semantic memory as such. In addition, individual instanced memory is needed for forming individual memory. In conclusion, the ontological approach can be further transferred to the field of building automation by representing domain-specific ontologies (individual) and upper ontologies (semantic).


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