Autonomous Learning And Chaining Of Motor Primitives Using The Free Energy Principle

# Autonomous learning and chaining of motor primitives using the Free Energy Principle

**arXiv ID:** 2005.05151
**Authors:** Louis Annabi, Alexandre Pitti, Mathias Quoy
**Published:** 2020-05-11T14:43:55Z
**Abstract:**
In this article, we apply the Free-Energy Principle to the question of motor primitives learning. An echo-state network is used to generate motor trajectories. We combine this network with a perception module and a controller that can influence its dynamics. This new compound network permits the autonomous learning of a repertoire of motor trajectories. To evaluate the repertoires built with our method, we exploit them in a handwriting task where primitives are chained to produce long-range sequences.

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## References

- [arXiv:2005.05151](http://arxiv.org/abs/2005.05151v1)