Cellular automata (CA) captivate researchers due to teh emergent, complex individualized behavior that simple global rules of interaction enact. Recent advances in the field have combined CA with convolutional neural networks to achieve self-regenerating images. This new branch of CA is called neural cellular automata [1]. The goal of this project is to use the idea of idea of neural cellular automata to grow prediction machines. We place many different convolutional neural networks in a grid. Each conv net cell outputs a prediction of what the next state will be, and minimizes predictive error. Cells received their neighbors' colors and fitnesses as input. Each cell's fitness score described how accurate its predictions were. Cells could also move to explore their environment and some stochasticity was applied to movement.

翻译：细胞自成一体(CA) 激发研究人员的动力, 原因是突如其来, 复杂的个体行为, 简单的全球互动规则 。 最近这个领域的进步将CA与进化神经网络相结合, 以实现自我再生图像。 CA的新分支称为神经细胞自成一体[1]。 该项目的目标是利用神经细胞自成一体的想法来培养预测机器。 我们把许多不同的神经神经神经网络放在一个网格中。 每个网格输出出对下一个状态的预测, 并最大限度地减少预测错误。 细胞接收到邻居的颜色和健康度作为输入。 每个细胞的健身分数描述了它的预测的准确度。 细胞还可以移动来探索环境, 一些随机性被用于运动 。