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Rolf M, Steil JJ, Gienger M.  2010.  Mastering Growth while Bootstrapping Sensorimotor Coordination. Int. Conf. on Epigenetic Robotics.
Rolf M, Steil JJ.  2014.  Efficient exploratory learning of inverse kinematics on a bionic elephant trunk. IEEE Trans. Neural Networks and Learning Systems. 25:1147–1160.
Rolf M, Steil JJ, Gienger M.  2010.  Bootstrapping inverse Kinematics with Goal Babbling. :147–154.
Rolf M, Gienger M, Steil JJ.  2013.  Robot control with bootstrapping inverse kinematics.
Rolf M, Steil JJ, Gienger M..  2010.  Goal Babbling permits direct learning of inverse kinematics. IEEE Trans. Autonomous Mental Development. 2:216–229.
Rolf M, Steil JJ.  2012.  Goal Babbling: a New Concept for Early Sensorimotor Exploration. Proceedings of Workshop on Developmental Robotics.
Ritter H, Haschke R, Röthling F, Steil JJ.  2011.  Manual Intelligence as a Rosetta Stone for Robot Cognition. Robotics Research. 66:135–146.
Ritter H, Weng S, Ontrup J, Steil JJ.  2006.  Gestalt Formation in a Competitive Layered Neural Architecture. Networks: From Biology to Theory. :163–191.
Ritter H, Haschke R, Steil JJ.  2007.  A Dual Interaction Perspective for Robot Cognition: Grasping as a "Rosetta Stone". Perspectives of Neural-Symbolic Integration. :159–178.
Ritter H, Steil JJ, Nölker C, Röthling F, McGuire PC.  2003.  Neural Architectures for Robotic Intelligence. Reviews in the Neurosciences. 14:121–143.
Ritter H, Haschke R, Steil JJ.  2009.  Trying to Grasp a Sketch of a Brain for Grasping. Creating Brain-Like Intelligence. :84–102.
Ritter H, Steil JJ, Sagerer G.  2010.  Mit Kopf, Körper und Hand: Herausforderungen Humanoider Roboter. Automatisierungstechnik, special issue on "humnoid robotics". 58:630–638.
Richter O, Reinhart F, Nease S, Steil JJ, Chicca E.  2015.  Device Mismatch in a Neuromorphic System Implements Random Features for Regression. Biomedical Circuits and Systems Conference (BioCAS), 2015 IEEE. :1–4.
Rhode M, Narioka K, Stein L, Steil JJ, Ernst M.  2019.  Goal-Related Feedback Guides Motor Exploration and Redundancy Resolution in Human Motor Skill Acquisition. PLOS Computational Biology. 15(3):1-27.
Reinhart F, Neumann K, Aswolinskiy W, Steil JJ, Hammer B.  2018.  Maschinelles Lernen in technischen Systemen. Steigerung der Intelligenz mechatronischer Systeme. :pp.73-118.
Reinhart F, Shareef Z, Steil JJ.  2017.  Hybrid Analytical and Data-driven Modeling for Feed-forward Robot Control. Sensors. 17(2)
Reinhart F, Steil JJ, Huntsberger TL, Stoica A.  2010.  Tacking reduces bow-diving of high-speed unmanned sea surface vehicles. Int. Symp. Learning and Adaptive Behavior in Robotic Systems. :177–182.
Reinhart F, Steil JJ.  2012.  Regularization and stability in reservoir networks with output feedback. Neurocomputing. 90:96–105.
Reinhart F, Steil JJ.  2011.  A constrained regularization approach for input-driven recurrent neural networks. Differential Equations and Dynamical Systems. 19:27–46.
Reinhart F, Steil JJ.  2014.  Efficient Policy Search with a Parameterized Skill Memory. :1400–1407.
Reinhart F, Steil JJ.  2009.  Attractor-based computation with reservoirs for online learning of inverse kinematics. European Symposium Artificial Neural Networks (ESANN). :257–262.
Reinhart F, Steil JJ.  2012.  Learning Whole Upper Body Control with Dynamic Redundancy Resolution in Coupled Associative Radial Basis Function Networks. IROS. :1487–1492.
Reinhart F, Steil JJ.  2016.  Hybrid Mechanical and Data-driven Modeling Improves Inverse Kinematic Control of a Soft Robot. Procedia Technology. 26:12–19.
Reinhart F, Steil JJ.  2011.  Neural learning and dynamical selection of redundant solutions for inverse kinematic control. Proc. IEEE Int. Conf. Humanoid Robots. :564–569.
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.