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arXiv · 2508.08091

Growing Reservoirs with Developmental Graph Cellular Automata

Matias Barandiaran·James Stovold
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Abstract

Developmental Graph Cellular Automata (DGCA) are a novel model for morphogenesis, capable of growing directed graphs from single-node seeds. In this paper, we show that DGCAs can be trained to grow reservoirs. Reservoirs are grown with two types of targets: task-driven (using the NARMA family of tasks) and task-independent (using reservoir metrics). Results show that DGCAs are able to grow into a variety of specialized, life-like structures capable of effectively solving benchmark tasks, statistically outperforming `typical' reservoirs on the same task. Overall, these lay the foundation for the development of DGCA systems that produce plastic reservoirs and for modeling functional, adaptive morphogenesis.

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Matias Barandiaran, James Stovold. 2025-08-11. Growing Reservoirs with Developmental Graph Cellular Automata. https://doi.org/10.1162/isal.a.854

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