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

• Ano de defesa: 2006
• Autor(a) principal: Abreu, Marjory Cristiany da Costa
• Orientador(a): Canuto, Anne Magaly de Paula
• 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: Sistemas multiagentes; Métodos de classificação; Métodos de negociação; Sistemas multi-classificadores; Ensemble
• Palavras-chave em Inglês: Multi-agent systems; Classification methods; Negotiation methods; Multi-classfiers systems; Ensemble
• Área do conhecimento CNPq: CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO::SISTEMAS DE COMPUTACAO
• Link de acesso: https://repositorio.ufrn.br/jspui/handle/123456789/18070

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