Canalization is a typical self-organization process leading to complementarity between parts and the whole. In the field of developmental biology, concerns about morphogenesis canalization are often framed as the French flag problem, questioning how each cell knows its own position in the whole system. Although chemical gradients have been suggested to provide positional information, there is no direct evidence that gradients are used to gain positional information. The chemical gradient hypothesis is based on the assumption that agents (e.g., cells) in a domain that locally interact with each other can generate a chemical gradient thanks to a global reference point. Instead of a chemical gradient, we here propose a model based on agents that are equipped with sociality that is based not on a global reference but rather on the ability to sense other neighboring agents, or potential resonance. The interaction among the agents with sociality, developed from undifferentiated types or tokens, is implemented using asynchronous updating automata equipped with potential resonance. We show that these automata can generate a French flag pattern that is very robust against perturbations without positional information by comparing automata with synchronous updating and asynchronous automata without potential resonance.
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