集体建构能从神经元胞自动机中学到什么?

A. Vardy
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引用次数: 0

摘要

神经细胞自动机(NCA)被训练成产生目标图像和形状,甚至在损伤后再生。这些都是非常有吸引力的特性,可以为集体机器人施工提供信息。我们讨论了可能对集体机器人结构有用的NCA概念,并讨论了形态发生和结构问题的不同之处。作为具体的第一步,我们提出了现有NCA模型的简化变体,以探索减少编码状态通道数量的后果。我们发现NCA仍然可以再现训练后的图像。这预示着将N - ca的想法转化为集体机器人建设的好兆头。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
What Can Collective Construction Learn from Neural Cellular Automata?
Neural Cellular Automata (NCA) have been trained to produce target images and shapes and even to regenerate after damage. These are highly attractive properties that can inform work on collective robotic construction. We discuss concepts from NCA that may be useful for collective robotic construction and discuss how the problems of morphogenesis and construction differ. As a concrete first step, we propose a simplified variant of an existing NCA model to explore the consequences of reducing the number of state channels encoded. We find that the NCA can still reproduce trained images. This bodes well for translating ideas from N CAs to collective robotic construction.
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