ML Anthology

Learning Cellular Automaton Dynamics with Neural Networks

N. H. Wulff, J A Hertz
NeurIPS 1992 pp. 631-638
/neurips/1992/wulff1992neurips-learning/

Abstract

We have trained networks of E - II units with short-range connec(cid:173) tions to simulate simple cellular automata that exhibit complex or chaotic behaviour. Three levels of learning are possible (in decreas(cid:173) ing order of difficulty): learning the underlying automaton rule, learning asymptotic dynamical behaviour, and learning to extrap(cid:173) olate the training history. The levels of learning achieved with and without weight sharing for different automata provide new insight into their dynamics.

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Text

Wulff and Hertz. "Learning Cellular Automaton Dynamics with Neural Networks." Neural Information Processing Systems, 1992.

Markdown

[Wulff and Hertz. "Learning Cellular Automaton Dynamics with Neural Networks." Neural Information Processing Systems, 1992.](https://mlanthology.org/neurips/1992/wulff1992neurips-learning/)

BibTeX

@inproceedings{wulff1992neurips-learning,
  title     = {{Learning Cellular Automaton Dynamics with Neural Networks}},
  author    = {Wulff, N. H. and Hertz, J A},
  booktitle = {Neural Information Processing Systems},
  year      = {1992},
  pages     = {631-638},
  url       = {https://mlanthology.org/neurips/1992/wulff1992neurips-learning/}
}