Biblio

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Reinhart F, Steil JJ.  2011.  Reservoir regularization stabilizes learning of Echo State Networks with output feedback. Proc. European Symposium on Artificial Neural Networks. :59–64.
Reinhart F, Steil JJ.  2011.  State prediction: a constructive method to program recurrent neural networks. Artificial Neural Networks and Machine Learning – ICANN 2011 : 21st International Conference on Artificial Neural Networks, Espoo, Finland, June 14-17, 2011, Proceedings, Part I. 6791:159–166.
Reinhart F, Steil JJ.  2008.  Recurrent neural associative learning of forward and inverse kinematics for movement generation of the redundant PA-10 robot. Int. Symp. Learning Adaptive Behavior in Robotic Systems, best paper award. 1:35–40.
Reinhart F, Lemme A, Steil JJ.  2012.  Representation and Generalization of Bi-manual Skills from Kinesthetic Teaching. IEEE-RAS International Conference on Humanoid Robots. :560–567.
Reinhart F, Steil JJ.  2015.  Efficient Policy Search in Low-dimensional Embedding Spaces by Generalizing Motion Primitives with a Parameterized Skill Memory. Autonomous Robots. 38:331–348.
Reinhart F, Steil JJ.  2009.  Reaching movement generation with a recurrent neural network based on learning inverse kinematics for the humanoid robot iCub. IEEE Conf. Humanoid Robotics. :323–330.
Reichler A-K, Gabriel F, Timmann F, Steil JJ, Dröder K.  2019.  An architecture for AutomationML-based constraint modelling and orchestration of Incremental Manufacturing. 7th CIRP Global Web Conference.
Rayyes R, Kubus D, Steil JJ.  2018.  Multi-Stage Goal Babbling for Learning Inverse Models Simultaneously.. IROS workshop.
Rayyes R, Donat H, Steil JJ.  In Press.  Efficient Online Interest-Driven Exploration for Developmental Robots. IEEE Trans. Cognitive and Developmental Systems.
Rayyes R, Steil JJ.  2019.  Online Associative Multi-Stage Goal Babbling Toward Versatile Learning of Sensorimotor Skills. Int. Conference Developmental Learning. :327-334.
Rayyes R, Kubus D, Hartmann C, Steil JJ.  2017.  Learning Inverse Statics Models Efficiently. arXiv.
Rayyes R, Steil JJ.  2016.  Goal Babbling with direction sampling for simultaneous exploration and learning of inverse kinematics of a humanoid robot. Proceedings of the workshop on New Challenges in Neural Computation. 4:56–63.
Rayyes R, Donat H, Steil JJ.  In Press.  Hierarchical Interest-Driven Associative Goal Babbling for Efficient Bootstrapping of Sensorimotor Skills. ICRA .
Rayyes R, Kubus D, Steil JJ.  2018.  Learning Inverse Statics Models Efficiently with Symmetry-Based Exploration. Frontiers in Neurorobotics.
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Pardowitz M, Haschke R, Steil JJ, Ritter H.  2008.  Gestalt-Based Action Segmentation for Robot Task Learning. IEEE-RAS 7th International Conference on Humanoid Robots (HUMANOIDS). :347–352.
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Ötting S, Gopinathan S, Maier GW, Steil JJ.  2017.  Why Criteria of Decision Fairness Should be Considered in Robot Design. Workshop Robots in Groups and Teams at ACM Conference on Computer Supported Cooperative Work and Social Computing.

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