Arquitetura baseada em ontologias de um agente RBC ontology-based architecture of a CBR agent

Case-Based Reasoning (CBR) is a problem solving paradigm where it is possible to use knowledge from past experiences to solve new situations. The CBR agent approach that combines agent autonomy with the problem solving model of CBR has been adequate for the development of complex systems. This paper proposes the architecture of a RBC agent whose main differential is the use of ontologies for representing the base case along with all the mechanisms that make up a CBR system. The proposed architecture besides promoting the reuse of the case ontology, unifies the software agent approach with CBR, a typical paradigm of human reasoning. All the CBR mechanisms are present in the proposed architecture: case representation, similarity analysis for cases retrieval, adaptation and cases learning, where the last two mechanisms are still being specified.