GNeurAge:一个基于智能体的任务分类进化系统

D. F. D. Oliveira, A. Canuto, André M. C. Campos
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引用次数: 14

摘要

研究了在多分类器系统结构中使用智能代理,以克服这些系统的一些缺点,从而提高这些系统的性能。基于此,NeurAge系统被提出。该系统在一些集中式和分布式分类任务中都取得了良好的效果。在本文中,使用进化技术在神经时代(GNeurAge)的功能进行了调查。为了做到这一点,我们将在两个不同的阶段使用遗传算法:在初始分类器的选择;以及在NeurAge功能(测试阶段)期间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
GNeurAge: An Evolutionary Agent-Based System for Classification Tasks
The use of intelligent agents in the structure of multiclassifier systems has been investigated in order to overcome some drawbacks of these systems and, as a consequence, to improve the performance of such systems. As a result of this, the NeurAge system was proposed. This system has presented good results in some centralized and distributed classification tasks. In this paper, an investigation of using evolutionary techniques in the functioning of the NeurAge (GNeurAge) is performed. In order to do this, we are going to use genetic algorithm in two different phases: in the choice of the initial classifier; and during the functioning of NeurAge (test phase).
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