神经细胞自动机（Neural Cellular Automata）可对信号作出响应
Neural Cellular Automata Can Respond to Signals
AI总结：
该研究验证了神经细胞自动机（NCAs）可经训练响应内部基因组编码信号与外部环境信号，能依内部信号长成不同形态、据外部信号变色，完善了人工形态发生模型并为其动态行为研究铺路。
摘要：
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有机体。本文中，我们证明NCAs可被训练以响应信号，研究采用两类信号：内部（基因组编码）信号与外部（环境）信号，信号仅在单个时间步内施加于单个像素。实验结果显示，NCAs能够依据内部信号生长为多种不同形态，还可根据外部信号改变颜色。总体而言，这些发现推动了NCAs作为人工形态发生模型的发展，也为未来将动态行为嵌入NCA模型的研究铺平了道路。代码与目标图像可通过GitHub获取：https://github.com/jstovold/ALIFE2023
英文摘要：
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
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
