EngramNCA: a Neural Cellular Automaton Model of Memory Transfer
Guichard, Etienne, Reimers, Felix, Kvalsund, Mia, Lepperød, Mikkel, Nichele, Stefano
–arXiv.org Artificial Intelligence
This study introduces EngramNCA, a neural cellular automaton (NCA) that integrates both publicly visible states and private, cell-internal memory channels, drawing inspiration from emerging biological evidence suggesting that memory storage extends beyond synaptic modifications to include intracellular mechanisms. The proposed model comprises two components: GeneCA, an NCA trained to develop distinct morphologies from seed cells containing immutable "gene" encodings, and GenePropCA, an auxiliary NCA that modulates the private "genetic" memory of cells without altering their visible states. This architecture enables the encoding and propagation of complex morphologies through the interaction of visible and private channels, facilitating the growth of diverse structures from a shared "genetic" substrate. EngramNCA supports the emergence of hierarchical and coexisting morphologies, offering insights into decentralized memory storage and transfer in artificial systems. These findings have potential implications for the development of adaptive, self-organizing systems and may contribute to the broader understanding of memory mechanisms in both biological and synthetic contexts. Data/Code: A web version of this article with videos is available here, while the Github repository is available here and the code is available on Colab here. Images that represent videos are hyperlinked to their respective video in the web version.
arXiv.org Artificial Intelligence
Apr-17-2025
- Country:
- Europe > Norway
- Eastern Norway > Oslo (0.05)
- North America > United States
- Massachusetts > Middlesex County > Cambridge (0.04)
- Europe > Norway
- Genre:
- Research Report > New Finding (0.68)
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