通过自动分类揭示莱尼亚参数空间结构，发现新类型孤立子。
Visualizing the Structure of Lenia Parameter Space
- 提出新方法自动划分莱尼亚系统为四类动力学行为
- 在未预期参数区域发现新型移动孤立子
- 可视化平台支持交互探索参数空间结构
连续元胞自动机正迅速流行，但对其行为的理论理解仍具挑战。以莱尼亚为例，关键开放问题包括：何为孤立子、参数空间整体结构如何，以及孤立子在其中的位置。本文提出一种新方法，可自动将莱尼亚系统分为四类定性不同的动力学类别。该方法能检测移动孤立子，并在网站 https://lenia-explorer.vercel.app/ 上实现参数空间结构的交互式可视化。结果为上述问题提供了新见解，发现某些此前认为不存在孤立子的参数区域中存在新类型孤立子，且不同核函数下相空间结构具有普遍性。
原文摘要 · Abstract (English)
Continuous cellular automata are rocketing in popularity, yet developing a theoretical understanding of their behaviour remains a challenge. In the case of Lenia, a few fundamental open problems include determining what exactly constitutes a soliton, what is the overall structure of the parameter space, and where do the solitons occur in it. In this abstract, we present a new method to automatically classify Lenia systems into four qualitatively different dynamical classes. This allows us to detect moving solitons, and to provide an interactive visualization of Lenia's parameter space structure on our website https://lenia-explorer.vercel.app/. The results shed new light on the above-mentioned questions and lead to several observations: the existence of new soliton families for parameters where they were not believed to exist, or the universality of the phase space structure across various kernels.
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