基于构造神经网络的建筑控制进化模糊系统

2005 International Symposium on Computational Intelligence in Robotics and Automation Pub Date : 2005-06-27 DOI:10.1109/CIRA.2005.1554333

R. Calvo, M. Figueiredo, Eric A. Antonelo

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引用次数: 6

摘要

这项工作描述了一个进化系统来控制一个用于自主导航的建设性神经网络的生长。分类器系统生成Takagi-Sugeno模糊规则并控制构造性神经网络的结构。移动机器人的性能指导着进化学习机制。实验表明，该分类器模糊系统在分析是否值得在结构中插入新的神经元方面是有效的。

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Evolutionary fuzzy system for architecture control in a constructive neural network

This work describes an evolutionary system to control the growth of a constructive neural network for autonomous navigation. A classifier system generates Takagi-Sugeno fuzzy rules and controls the architecture of a constructive neural network. The performance of the mobile robot guides the evolutionary learning mechanism. Experiments show the efficiency of the classifier fuzzy system for analyzing if it is worth inserting a new neuron into the architecture.

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2005 International Symposium on Computational Intelligence in Robotics and Automation

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