Evolution must explain both its ability to produce beneficial innovations as well as preserve organisms’ existing functional adaptedness to their environment. A proposed mechanism which resolves this tension is the concept of neutral networks, wherein mutations are not strictly beneficial or deleterious but neutral in their effect on organisms’ adaptedness. Neutral networks have been shown to be both prevalent and vast at multiple levels of biological organization. Additionally, there is much philosophical debate regarding how information flows between and across these levels of organization in reality. However, how to pragmatically engineer systems with multiscale structure to harness the inherent robustness that neutral networks confer remains largely unexplored. Here we show that, in hierarchical neural cellular automata (HNCA), various inter-scale connectivity architectures support mutational robustness and evolvability through the formation of neutral networks, wherein similar functional outcomes (e.g., morphogenesis, homeostasis) are achievable through diverse pathways of multiscale interactions. These findings can help inform the way we engineer artificial multiscale systems, e.g. hierarchical arrangements of robots. Operationalizing these insights may offer new ways of designing and engineering intelligent, robust, and adaptive machines. Additionally, the connection structures we explore have philsophical implications which may inform discussions of causal emergence in complex systems.

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