The balance between initial training and lifelong adaptation in evolving robot controllers
The balance between initial training and lifelong adaptation in evolving robot controllers
复制标题
不断发展的机器人控制器中初始训练和终身适应之间的平衡
DOI：
10.1109/tsmcb.2005.859082
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发表时间：
2006
期刊：
影响因子：
--
通讯作者：
Myra S. Wilson
中科院分区：
文献类型：
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作者：
Joanne H. Walker;Simon M. Garrett;Myra S. Wilson
机器人研究的一个中心目标是设计出能够在真实的世界中工作的机器人，而这个真实的世界在本质上是高度可变的。因此，研究人员面临的一个重要挑战是生产出能够在环境稳定时提高性能并在环境变化时适应的机器人。本文报告的实验表明，进化方法可以提供终身适应机器人，以及这种进化过程是如何体现在机器人本身。一个独特的组合的培训和终身适应的使用，本文强调了培训的重要性，这种方法。
A central aim of robotics research is to design robots that can perform in the real world; a real world that is often highly changeable in nature. An important challenge for researchers is therefore to produce robots that can improve their performance when the environment is stable, and adapt when the environment changes. This paper reports on experiments which show how evolutionary methods can provide lifelong adaptation for robots, and how this evolutionary process was embodied on the robot itself. A unique combination of training and lifelong adaptation are used, and this paper highlights the importance of training to this approach.