Self-Organized Construction by Minimal Surprise

Tanja Katharina Kaiser, Heiko Hamann
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引用次数: 2

Abstract

For the robots to achieve a desired behavior, we can program them directly, train them, or give them an innate driver that makes the robots themselves desire the targeted behavior. With the minimal surprise approach, we implant in our robots the desire to make their world predictable. Here, we apply minimal surprise to collective construction. Simulated robots push blocks in a 2D torus grid world. In two variants of our experiment we either allow for emergent behaviors or predefine the expected environment of the robots. In either way, we evolve robot behaviors that move blocks to structure their environment and make it more predictable. The resulting controllers can be applied in collective construction by robots.
最小意外的自组织结构
为了让机器人实现期望的行为,我们可以直接给它们编程,训练它们,或者给它们一个天生的驱动力,让机器人自己渴望目标行为。用最小的惊喜方法,我们给机器人植入了让他们的世界可预测的愿望。在这里,我们将最小的惊喜运用到集体建设中。模拟机器人在二维环面网格世界中推块。在我们实验的两个变体中,我们要么允许突发行为,要么预先定义机器人的预期环境。无论是哪种方式,我们都在进化机器人的行为,移动方块来构建它们的环境,使其更可预测。所得到的控制器可以应用于机器人的集体施工。
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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