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.

翻译：本文介绍了EINCASM，一种采用新颖框架研究类似黏菌生物体中涌现智能的原型系统。EINCASM通过NEAT进化神经细胞自动机，在营养与能量成本的约束下最大化细胞生长。这些生物体利用物理模拟流体输送营养物质及类化学信号，以协调自身生长并适应复杂多变的环境。我们的框架为研究谜题、物理、通信、竞争及动态开放环境如何共同促进智能行为的涌现奠定了基础。我们提出了针对此类生物体智能的初步测试方法，并建议未来采用EINCASM构建更强大的系统，以更深入地理解分布式动态系统中的智能。