  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.
