Neural Cellular Automata (NCAs) are a model of morphogenesis, capable of growing two-dimensional artificial organisms from a single seed cell. In this paper, we show that NCAs can be trained to respond to signals. Two types of signal are used: internal (genomically-coded) signals, and external (environmental) signals. Signals are presented to a single pixel for a single timestep. Results show NCAs are able to grow into multiple distinct forms based on internal signals, and are able to change colour based on external signals. Overall these contribute to the development of NCAs as a model of artificial morphogenesis, and pave the way for future developments embedding dynamic behaviour into the NCA model. Code and target images are available through GitHub: https://github.com/jstovold/ALIFE2023

翻译：神经细胞自动机（Neural Cellular Automata，NCAs）是一种形态发生模型，能够从单个种子细胞生长出二维人工生物体。本文表明，NCAs可通过训练来响应信号。研究使用两种信号：内部信号（基因组编码）与外部信号（环境信号）。信号在单个时间步长内作用于单个像素。实验结果表明，NCAs能够根据内部信号生长为多种不同形态，并能依据外部信号改变颜色。这些成果推动了NCAs作为人工形态发生模型的发展，并为未来将动态行为嵌入NCA模型的研究奠定了基础。相关代码与目标图像可通过GitHub获取：https://github.com/jstovold/ALIFE2023