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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Analisando o desempenho do ClassAge: um sistema multiagentes para classifica??o de padr?es

Abreu, Marjory Cristiany da Costa 26 October 2006 (has links)
Made available in DSpace on 2014-12-17T15:48:05Z (GMT). No. of bitstreams: 1 MarjoryCCA.pdf: 917121 bytes, checksum: 918ccb19adcf29ebd6cdbf1f3ac97310 (MD5) Previous issue date: 2006-10-26 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior / 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 / A utiliza??o de sistemas baseados no paradigma dos agentes para resolu??o de problemas de reconhecimento de padr?es vem sendo propostos com o intuito de resolver, ou atenuar, o problema de tomada de decis?o centralizada dos sistemas multi-classificadores e, como consequ?ncia, melhorar sua capacidade de classifica??o. Com a inten??o de solucionar este problema, o Sistema NeurAge foi proposto. Este sistema ? composto por agentes neurais que podem se comunicar e negociar um resultado comum para padr?es de teste. No Sistema NeurAge, os m?todos de negocia??o s?o muito importantes para prover uma melhor precis?o ao sistema, pois os agentes necessitam alcan?ar a melhor solu??o e resolver conflitos, quando estes existem, em rela??o a um problema. Esta disserta??o apresenta uma extens?o do Sistema NeurAge que pode utilizar qualquer tipo de classificador e agora ser? chamado de Sistema ClassAge. Aqui ? feita uma an?lise do comportamento do Sistema ClassAge diante de v?rias modifica??es na topologia e nas configura??es dos componentes deste sistema

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