Analisando o desempenho do ClassAge: um sistema multiagentes para classificação de padrões

Detalhes bibliográficos
Ano de defesa: 2006
Autor(a) principal: Abreu, Marjory Cristiany da Costa
Orientador(a): Canuto, Anne Magaly de Paula
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Federal do Rio Grande do Norte
Programa de Pós-Graduação: Programa de Pós-Graduação em Sistemas e Computação
Departamento: Ciência da Computação
País: BR
Palavras-chave em Português:
Palavras-chave em Inglês:
Área do conhecimento CNPq:
Link de acesso: https://repositorio.ufrn.br/jspui/handle/123456789/18070
Resumo: The use of multi-agent systems for classification tasks has been proposed in order to overcome some drawbacks of multi-classifier systems and, as a consequence, to improve performance of such systems. As a result, the NeurAge system was proposed. This system is composed by several neural agents which communicate and negotiate a common result for the testing patterns. In the NeurAge system, a negotiation method is very important to the overall performance of the system since the agents need to reach and agreement about a problem when there is a conflict among the agents. This thesis presents an extensive analysis of the NeurAge System where it is used all kind of classifiers. This systems is now named ClassAge System. It is aimed to analyze the reaction of this system to some modifications in its topology and configuration