# Reservoir computing

tags
Machine learning, Unconventional computing, Unsupervised learning

Reservoir computing is a term used to describe a class of machine learning algorithms that rely on transient dynamics of a dynamical system to implement and manipulate goal-related information.

The most famous example is echo-state networks, which uses random recurrent neural networks as reservoirs, but other dynamical systems can also be used.

## Reservoir computing with cellular automata

Reservoir computing can use cellular automata as the reservoir. Some citations (Nichele and Molund 2017; Yilmaz 2014; Morán, Frasser, and Rosselló 2018; Babson, Teuscher, and 2019).

## Bibliography

1. . . "Reservoir Computing with Complex Cellular Automata". Complex Systems 28 (4):433–55. DOI.

2. . . “Unsupervised Reservoir Computing for Solving Ordinary Differential Equations”. arXiv:2108.11417 [Physics]. http://arxiv.org/abs/2108.11417.

3. . . “Reservoir Computing Hardware with Cellular Automata”. arXiv:1806.04932 [Nlin]. http://arxiv.org/abs/1806.04932.

4. . . “Deep Reservoir Computing Using Cellular Automata”. arXiv:1703.02806 [Cs]. http://arxiv.org/abs/1703.02806.

5. . . “Reservoir Computing Using Cellular Automata”. arXiv:1410.0162 [Cs]. http://arxiv.org/abs/1410.0162.