**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 evalua...
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# 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.
## Skill Description
This skill is generated from the arXiv paper: Autonomous learning and chaining of motor primitives using the Free Energy Principle (2005.05151).
## How to Use
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## References
- [arXiv:2005.05151](http://arxiv.org/abs/2005.05151v1)
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