细胞自动机_神经细胞自动机用于艺术娱乐

细胞自动机

The article will briefly introduce the field of Cellular Automata (CA), along with a Neural Network approach. The outputs of this work are not simply images. They are some form of a virtual organism that, similar to a living body, grows, and responds to changes. This is an experimental work that hopes to encode information in a genome-like fashion.

本文将简要介绍细胞自动机(CA)领域以及神经网络方法。 这项工作的输出不只是图像。 它们是虚拟生物的某种形式，类似于生物体，可以生长并响应变化。 这是一项实验性工作，希望以类似基因组的方式编码信息。

At the end of this article, we won't be able to create a virtual human living in San Junipero (shout-out to Black Mirrors fans). However, we will be able to present a recreation of Keith Haring’s icon series (1990). These icons will grow from a single cell until they reach a saturation point, where the single-cell becomes one multicellular entity.

在本文的最后，我们将无法在San Junipero中创建虚拟人(向Black Mirrors粉丝大喊大叫)。 但是，我们将能够介绍Keith Haring的偶像系列(1990年)。 这些图标将从单个单元格增长到达到饱和点，在该点上，单个单元格将成为一个多细胞实体。

If you are not interested in the technicalities behind the Neural Network architecture feel free to skip sections with titles starting by “CNN:”. I set the code used for this project on a Colab notebook, which can be used to create similar figures and images for user-defined inputs. The notebook is an edited version of Mordvintsev’s work on Growing Neural Cellular Automata [1].

如果您对神经网络体系结构背后的技术不感兴趣，请随时跳过标题以“ CNN： ”开头的部分。 我在Colab 笔记本上设置了用于该项目的代码，该代码可用于为用户定义的输入创建相似的图形和图像。 该笔记本是Mordvintsev关于“神经细胞自动机的成长” [1]的编辑版本。

Public Projects Archive. Bottom image by author) 公共项目档案 。底部图像由作者提供)

In the early 1950s, Rosalind Franklin, Francis Crick, and James Watson’s collaboration led to the discovery of the DNA [2]. This discovery did create not only the most significant milestone in the development of modern biology but also shaped other fields such as computer science.

1950年代初期， 罗莎琳德·富兰克林 ，弗朗西斯·克里克和詹姆斯·沃森 合作导致了DNA的发现[2]。 这一发现不仅创造了现代生物学发展中最重要的里程碑，而且还塑造了计算机科学等其他领域。

Public Domain. 公共领域 。

Although computer science seemed disconnected entirely from biology, computer scientists like John von Neumann, Stanislaw Ulam, and S. Wolfram were impressed by the efficiency and complexity of biological systems [3]. They painted a model that interprets the newly-founded DNA role and translates the molecular biology architecture to serve computing purposes. According to their understanding at that time, a living body is governed by a single algorithm (DNA), and several functionalities (biochemical operations), which enable nature to present a continuous and responsive model (a biological organism). Hence, life has found a way to compress large information and encode complex behaviors only by using these two principles. This understanding is the foundation of Cellular Automata (CA). Hence, CA is an exercise of experimental dynamics in computer science algorithms in the hope of reconstructing information into a genome-encoded cellular form.

尽管计算机科学似乎与生物学完全脱节，但是像约翰·冯·诺依曼，斯坦尼斯瓦夫·乌兰姆和S·沃尔夫拉姆这样的计算机科学家对生物系统的效率和复杂性印象深刻[3]。 他们绘制了一个模型，该模型解释了新近成立的DNA角色并转换了分子生物学体系结构以用于计算目的。 根据他们当时的理解，活体由单一算法(DNA)和多种功能(生化操作)控制，这些功能使自然界能够呈现出连续且ReactSwift的模型(生物体)。 因此，生活找到了一种仅通过使用这两个原理来压缩大量信息并编码复杂行为的方法。 这种了解是细胞自动机(CA)的基础。 因此，CA是计算机科学算法中实验动态的一种练习，希望将信息重构为基因组编码的细胞形式。

细胞自动机简介 (Introduction to Cellular Automaton)

A cellular automaton is a continuous state of a set of cells (elements of a grid) starting from a seed that can be either a single cell or several cells. A set of cells at time “t+1” is an update of the set at “t” according to an update “rule”. The update rule involves calculations that depend on neighboring cells. There are three standard definitions of a neighbor cell.

细胞自动机是从种子开始的一组细胞(网格元素)的连续状态，种子可以是单个细胞也可以是多个细胞。 在时间“ t + 1”的一组小区是根据更新“ 规则”在“ t”的一组小区的更新。 更新规则涉及取决于相邻小区的计算。 邻居小区有三个标准定义。

Figure 3: Examples for the different neighborhood, (Photo by the author)

图3：不同邻域的示例，(作者提供的照片)

According to each different type of neighborhood, a varied selection of cells (colored grey) contributes to the update of a specific cell (colored black). Thus, the state or values a cell holds directly affects the other cells. Hence, a cellular automaton evolves as a continuous entity. The influence of neighbors on a cell differs according to the type of grid. The best way to illustrate this is by considering a 1-dimensional grid. In the animation below, all the cells occupy one line. Each cell can only have a value of 0 or 1.

根据每种不同的邻域类型，单元格(灰色)的变化选择有助于特定单元格(黑色)的更新。 因此，一个单元格保持的状态或值直接影响其他单元格。 因此，细胞自动机发展成为一个连续的实体。 邻居对小区的影响根据网格的类型而不同。 最好的说明方法是考虑一维网格。 在下面的动画中，所有单元格都占据一行。 每个单元格只能具有0或1的值。

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