Emergent Models (EMs) are a machine learning paradigm based on simple yet open-ended substrates, such as cellular automata, in which modeling is treated not as the learning of a closed-form input-output map but as the emergence, within simple dynamical systems, of computational behaviors that solve external tasks. Such...
Giacomo Bocchese, Nicola Giacobbo, Etienne Guichard et al.· 0 citations
Emergent Models (EMs) are a machine learning paradigm based on simple yet open-ended substrates, such as cellular automata, in which modeling is treated not as the learning of a closed-form input-output map but as the emergence of computational behaviors in simple dynamical systems. Such substrates are often based on t...
Giacomo Bocchese, Nicola Giacobbo, Etienne Guichard et al.· IEEE Symposium on Artificial...· 0 citations
Modern deep learning models achieve impressive generalization through over-parameterization, but this paradigm often struggles with overfitting and memorization in few-shot regimes. Neural Cellular Automata (NCAs) offer a highly parameter-efficient alternative, yet research has focused primarily on their output, leavin...
Etienne Guichard, Stefano Nichele· 0 citations
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