- tags
- Cellular automata as CNNs
- source
- (Gilpin 2018)
Summary
This is one of the only attempt to represent a CA rule as a CNN I have come across. The author uses a deep CNN to learn a rule and studies various information-theoretic quantities in the activation patterns to evaluate the complexity of the rules.
Comments
I am personally very interested by the paper since it is an interesting direction for creating neural-network based rules that can be sampled and efficiently stored and applied. This work is also cited in (Mordvintsev et al. 2020).
Bibliography
Gilpin, William. 2018. “Cellular Automata as Convolutional Neural Networks.” arXiv:1809.02942 [Cond-Mat, Physics:Nlin, Physics:Physics], September.
Mordvintsev, Alexander, Ettore Randazzo, Eyvind Niklasson, and Michael Levin. 2020. “Growing Neural Cellular Automata.” Distill 5 (2):e23.