This paper presents Coralai, a framework for exploring diverse ecosystems of
Neural Cellular Automata (NCA). Organisms in Coralai utilize modular,
GPU-accelerated Taichi kernels to interact, enact environmental changes, and
evolve through local survival, merging, and mutation operations implemented
with HyperNEAT and PyTorch. We provide an exploratory experiment implementing
physics inspired by slime mold behavior showcasing the emergence of competition
between sessile and mobile organisms, cycles of resource depletion and
recovery, and symbiosis between diverse organisms. We conclude by outlining
future work to discover simulation parameters through measures of multi-scale
complexity and diversity. Code for Coralai is available at
this https URL , video demos are available at
this https URL .

Coralai 是一个用于探索神经元元胞自动机（NCA）多样化生态系统的框架，通过使用模块化的 GPU 加速 Taichi 内核，以 HyperNEAT 和 PyTorch 实现的局部存活、合并和变异操作，实现了生物在 Coralai 中的相互作用、环境变化和进化。通过模拟黏菌行为的物理实验，展示了固定和移动生物之间的竞争、资源消耗和恢复循环以及多样化生物之间的共生关系。同时提出未来研究工作的设想，通过多尺度复杂性和多样性的度量来发现模拟参数。Coralai 的代码可在该 URL 获取，视频演示可在该 URL 获取。

Coralai: 具有自主进化的体验感知神经元元胞自动机生态系统

Coralai: Intrinsic Evolution of Embodied Neural Cellular Automata  Ecosystems

Most animals possess the ability to actuate a vast diversity of movements,
ostensibly constrained only by morphology and physics. In practice, however, a
frequent assumption in behavioral science is that most of an animal's
activities can be described in terms of a small set of stereotyped motifs. Here
we introduce a method for mapping the behavioral space of organisms, relying
only upon the underlying structure of postural movement data to organize and
classify behaviors. We find that six different drosophilid species each perform
a mix of non-stereotyped actions and over one hundred hierarchically-organized,
stereotyped behaviors. Moreover, we use this approach to compare these species'
behavioral spaces, systematically identifying subtle behavioral differences
between closely-related species.

通过昆虫的姿势运动数据研究动物的行为，发现六种果蝇物种每种都表现出非成规动作和超过一百个等级组织的定型行为，此方法可以比较这些物种行为空间并系统地确定近缘物种间微妙的行为差异。

自由移动果蝇的刻板行为映射

Mapping the stereotyped behaviour of freely-moving fruit flies

In a cell or microorganism the processes that generate mass, energy,
information transfer, and cell fate specification are seamlessly integrated
through a complex network of various cellular constituents and reactions.
However, despite the key role these networks play in sustaining various
cellular functions, their large-scale structure is essentially unknown. Here we
present the first systematic comparative mathematical analysis of the metabolic
networks of 43 organisms representing all three domains of life. We show that,
despite significant variances in their individual constituents and pathways,
these metabolic networks display the same topologic scaling properties
demonstrating striking similarities to the inherent organization of complex
non-biological systems. This suggests that the metabolic organization is not
only identical for all living organisms, but complies with the design
principles of robust and error-tolerant scale-free networks, and may represent
a common blueprint for the large-scale organization of interactions among all
cellular constituents.

本文首次系统比较了 43 种不同生命领域内生物代谢网络的数学结构，并发现虽然组成和途径不同，但这些代谢网络却表现出同样的拓扑特性，显示出与复杂非生物系统的内在组织相似的架构。这表明代谢组织不仅对于所有生物有着相同的属性，而且符合鲁棒和容错无限网络的设计原则，并可能为所有细胞成分间的大规模相互作用的组织提供通用蓝图。