Artificial neurogenesis: an application to autonomous robotics

O. Michel, P. Collard
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引用次数: 14

Abstract

A lot of research papers focus on the challenging problem of the combination of genetic algorithms and artificial neural networks. Developmental and molecular biology may be a source of inspiration for designing powerful artificial neurogenesis systems allowing the generation of complex modular structures. This paper describes in detail such a neurogenesis model associated with an evolutionary process and its application to the control of a mobile robot. Early results demonstrate the surprising efficiency of this methodology and give hints to continue the research towards the generation of more complex adaptive neural networks.
人工神经发生:在自主机器人中的应用
遗传算法与人工神经网络相结合这一具有挑战性的问题是许多研究论文关注的焦点。发育和分子生物学可能是设计强大的人工神经发生系统的灵感来源,允许产生复杂的模块化结构。本文详细介绍了这种与进化过程相关的神经发生模型及其在移动机器人控制中的应用。早期的结果证明了这种方法的惊人效率,并为继续研究更复杂的自适应神经网络提供了线索。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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