提出流守恒连续元胞自动机，可生成复杂自组织生命形态并实现多物种演化模拟。
Flow-Lenia: Emergent evolutionary dynamics in mass conservative continuous cellular automata
- 基于质量守恒设计新更新规则，使系统能自发形成空间局域模式。
- 优化参数后可生成具复杂行为的类生命体，如自我复制与适应性运动。
- 模型内嵌参数演化机制，支持多物种共存与进化动态研究，适合人工生命探索者。
人工生命的核心目标是构建能自发产生生命特征（如自维持、自复制、演化与开放性）的系统。尽管已有多种模型，元胞自动机因其在自繁殖与自组织现象研究中的优势而尤为重要。连续型元胞自动机如Lenia已展现出类似生物有机体的生命样态，称为‘生物体’。本文提出Flow-Lenia，一种质量守恒的Lenia扩展。实验表明其能有效生成具有复杂行为的空间局域模式（SLPs），并通过优化更新规则参数生成具备兴趣行为的复杂生物体。进一步地，我们证明了模型参数可被嵌入系统动态中，实现多物种仿真。结合演化活跃度框架及其他度量指标，揭示了该系统中涌现的演化动力学过程。
原文摘要 · Abstract (English)
Central to the artificial life endeavour is the creation of artificial systems spontaneously generating properties found in the living world such as autopoiesis, self-replication, evolution and open-endedness. While numerous models and paradigms have been proposed, cellular automata (CA) have taken a very important place in the field notably as they enable the study of phenomenons like self-reproduction and autopoiesis. Continuous CA like Lenia have been showed to produce life-like patterns reminiscent, on an aesthetic and ontological point of view, of biological organisms we call creatures. We propose in this paper Flow-Lenia, a mass conservative extension of Lenia. We present experiments demonstrating its effectiveness in generating spatially-localized patters (SLPs) with complex behaviors and show that the update rule parameters can be optimized to generate complex creatures showing behaviors of interest. Furthermore, we show that Flow-Lenia allows us to embed the parameters of the model, defining the properties of the emerging patterns, within its own dynamics thus allowing for multispecies simulations. By using the evolutionary activity framework as well as other metrics, we shed light on the emergent evolutionary dynamics taking place in this system.
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