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.

翻译：连续型元胞自动机正迅速普及，然而对其行为建立理论理解仍具挑战性。以 Lenia 为例，若干基础性开放问题包括：明确孤子的确切构成、参数空间的整体结构为何，以及孤子在其中的分布位置。本文提出一种新方法，可将 Lenia 系统自动划分为四个具有质差别的动力学类别。该方法使我们能够检测运动孤子，并在网站 https://lenia-explorer.vercel.app/ 上提供 Lenia 参数空间结构的交互式可视化。研究结果为上述问题提供了新见解，并得出若干发现：在原本认为不存在孤子的参数区域发现了新的孤子族，以及不同核函数间相空间结构具有普适性。