This paper presents EINCASM, a prototype system employing a novel framework for studying emergent intelligence in organisms resembling slime molds. EINCASM evolves neural cellular automata with NEAT to maximize cell growth constrained by nutrient and energy costs. These organisms capitalize physically simulated fluid to transport nutrients and chemical-like signals to orchestrate growth and adaptation to complex, changing environments. Our framework builds the foundation for studying how the presence of puzzles, physics, communication, competition and dynamic open-ended environments contribute to the emergence of intelligent behavior. We propose preliminary tests for intelligence in such organisms and suggest future work for more powerful systems employing EINCASM to better understand intelligence in distributed dynamical systems.

本文介绍EINCASM，一个采用新框架的原型系统，用于研究类似史莱姆菌的生物中出现的智能。该框架基于神经元细胞自动机，通过最大化细胞生长来控制营养和能量成本。这些生物利用物理模拟的流体来运输营养和化学信号，并在复杂、多变的环境中进行生长和适应。我们的框架为研究拼图、物理、通信、竞争和动态开放环境如何促进智能行为的出现建立了基础。我们提出了在这些生物中测试智能的初步方法，并建议未来的工作：使用EINCASM来更好地理解分布式动力系统中的智能行为。

神经细胞自动机黏菌中的新兴智能