Active learning of inverse models with intrinsically motivated goal exploration in robots

@article{Baranes2013ActiveLO,
  title={Active learning of inverse models with intrinsically motivated goal exploration in robots},
  author={Adrien Baranes and Pierre-Yves Oudeyer},
  journal={Robotics Auton. Syst.},
  year={2013},
  volume={61},
  pages={49-73}
}
  • Adrien Baranes, Pierre-Yves Oudeyer
  • Published 2013
  • Computer Science
  • Robotics Auton. Syst.
  • We introduce the Self-Adaptive Goal Generation Robust Intelligent Adaptive Curiosity (SAGG-RIAC) architecture as an intrinsically motivated goal exploration mechanism which allows active learning of inverse models in high-dimensional redundant robots. [...] Key Method For both learning and generalization, the system leverages regression techniques which allow to infer the motor policy parameters corresponding to a given novel parameterized task, and based on the previously learnt correspondences between policy…Expand Abstract

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