EngramNCA: a Neural Cellular Automaton Model of Memory Transfer
This work addresses memory storage and transfer for adaptive, self-organizing systems, offering insights into biological and synthetic contexts, but it is incremental as it builds on existing neural cellular automaton concepts.
The study tackled the problem of modeling memory transfer in artificial systems by introducing EngramNCA, a neural cellular automaton with public and private memory channels, which enabled the encoding and propagation of complex morphologies from shared genetic substrates, resulting in the emergence of hierarchical and coexisting structures.
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.