[1]

Jonas Buchli, Freek Stulp, Evangelos Theodorou, and Stefan Schaal. Learning variable impedance control. International Journal of Robotics Research, 30(7):820–833, 2011.

[2]

Bruno da Silva, George Konidaris, and Andrew G. Barto. Learning parameterized skills. In John Langford and Joelle Pineau, editors, Proceedings of the 29th International Conference on Machine Learning (ICML-12), ICML '12, pages 1679–1686, New York, NY, USA, July 2012. Omnipress.

[3]

A. J. Ijspeert, J. Nakanishi, and S. Schaal. Movement imitation with nonlinear dynamical systems in humanoid robots. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 2002.

[4]

A. Ijspeert, J. Nakanishi, P Pastor, H. Hoffmann, and S. Schaal. Dynamical Movement Primitives: Learning attractor models for motor behaviors. Neural Computation, 25(2):328–373, 2013.

[5]

M. Kalakrishnan, L. Righetti, P. Pastor, and S. Schaal. Learning force control policies for compliant manipulation. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2011), 2011.

[6]

Tomas Kulvicius, KeJun Ning, Minija Tamosiunaite, and Florentin Wörgötter. Joining movement sequences: Modified dynamic movement primitives for robotics applications exemplified on handwriting. IEEE Transactions on Robotics, 28(1):145–157, 2012.

[7]

T Matsubara, S Hyon, and J Morimoto. Learning parametric dynamic movement primitives from multiple demonstrations. Neural Networks, 24(5):493–500, 2011.

[8]

Freek Stulp and Olivier Sigaud. Path integral policy improvement with covariance matrix adaptation. In Proceedings of the 29th International Conference on Machine Learning (ICML), 2012.

[9]

Freek Stulp and Olivier Sigaud. Policy improvement methods: Between black-box optimization and episodic reinforcement learning. hal-00738463, 2012.

[10]

Freek Stulp and Olivier Sigaud. Robot skill learning: From reinforcement learning to evolution strategies. Paladyn. Journal of Behavioral Robotics, 4(1):49–61, September 2013.

[11]

Freek Stulp and Olivier Sigaud. Many regression algorithms, one unified model – a review. Neural Networks, 2015.

[12]

Freek Stulp, Gennaro Raiola, Antoine Hoarau, Serena Ivaldi, and Olivier Sigaud. Learning compact parameterized skills with a single regression. In IEEE-RAS International Conference on Humanoid Robots, 2013.

[13]

Freek Stulp, Laura Herlant, Antoine Hoarau, and Gennaro Raiola. Simultaneous on-line discovery and improvement of robotic skill options. In International Conference on Intelligent Robots and Systems (IROS), 2014.

[14]

Freek Stulp. Adaptive exploration for continual reinforcement learning. In International Conference on Intelligent Robots and Systems (IROS), pages 1631–1636, 2012.