Active Contextual Entropy Search

@article{Metzen2015ActiveCE,
  title={Active Contextual Entropy Search},
  author={Jan Hendrik Metzen},
  journal={CoRR},
  year={2015},
  volume={abs/1511.04211}
}
Contextual policy search allows adapting robotic movement primitives to different situations. For instance, a locomotion primitive might be adapted to different terrain inclinations or desired walking speeds. Such an adaptation is often achievable by modifying a small number of hyperparameters. However, learning, when performed on real robotic systems, is typically restricted to a small number of trials. Bayesian optimization has recently been proposed as a sample-efficient means for contextual… CONTINUE READING
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Gaussian process optimization in the bandit setting: No regret and experimental design

  • N. Srinivas, A. Krause, M. Seeger
  • In Proceedings of the 27th International…
  • 2010
Highly Influential
3 Excerpts

COMPI: Development of a 6-DOF compliant robot arm for humanrobot cooperation

  • V. Bargsten, J. de Gea
  • In Proceedings of the 8th International Workshop…
  • 2015
1 Excerpt

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