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Seidel D, Emmerich C, Steil JJ.  2014.  Model-free Path Planning for Redundant Robots using Sparse Data from Kinesthetic Teaching. Proc. of the Int. Conference on Intelligent Robots and Systems (IROS). :4381–4388.
Shareef Z, Steil JJ.  2016.  Trajectory Optimization of COmpliant HuMANoid (COMAN) Robot Arm using Path Parameter based Dynamic Programming. Proc. IEEE Humanoids. :705–710.
Shareef Z, Reinhart F, Steil JJ.  2016.  Generalizing the Inverse Dynamic Model of KUKA LWR IV+ for Load Variations using Regression in the Model Space. Proceedings of IEEE Int. Conf. Intelligent Robots and Systems. :606–611.
Shareef Z, Mohammadi P, Steil JJ.  2016.  Improving the Inverse Dynamics Model of the KUKA LWR IV+ using Independent Joint Learning. Proceedings 7th IFAC Symposium on Mechatronic Systems. :507––512.
Soltoggio A, Steil JJ.  2013.  Solving the distal reward problem with rare correlations. Neural Computation. 25:940–978.
Soltoggio A, Reinhart F, Lemme A, Steil JJ.  2013.  Learning the rules of a game: neural conditioning in human-robot interaction with delayed rewards.
Soltoggio A, Lemme A, Steil JJ.  2012.  Using movement primitives in interpreting and decomposing complex trajectories in learning-by-doing. :1427–1433.
Soltoggio A, Steil JJ.  2012.  How Rich Motor Skills Empower Robots at Last: Insights and Progress of the AMARSi Project. KI- Künstliche Intelligenz. 26:407–410.
Soltoggio A, Lemme A, Reinhart F, Steil JJ.  2013.  Rare neural correlations implement robotic conditioning with reward delays and disturbances. Frontiers in Neurorobotics. 7:6.
Steffen JFrederik, Pardowitz M, Steil JJ, Ritter H.  2010.  Neural competition for motion segmentation. 18th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN). :59–64.
Steffen JFrederik, Pardowitz M, Steil JJ, Ritter H.  2011.  Integrating Feature Maps and Competitive Layer Architectures For Motion Segmentation. Neurocomputing. 74:1372–1381.
Steil JJ.  2007.  Online reservoir adaptation by intrinsic plasticity for backpropagation-decorrelation and echo state learning. Neural Networks. 20:353–364.
Steil JJ, Kõiva R, Sperduti A.  2006.  Unsupervised Clustering of Continuous Trajectories of Kinematic Trees with SOM-SD. Proc. European Symposium on Artificial Neural Networks.
Steil JJ.  1999.  Input-Output Stability of Recurrent Neural Networks.
Steil JJ, Heidemann G, Jockusch J, Rae R, Jungclaus N, Ritter H.  2001.  Guiding Attention for Grasping Tasks by Gestural Instruction: The GRAVIS-Robot Architecture. Proc. Int. Conf. Intelligent Robots and Sytems. :1570–1577.
Steil JJ, Krüger S.  2013.  Lernen und Sicherheit in Interaktion mit Robotern aus Maschinensicht. Robotik und Gesetzgebung. 2:51–71.
Steil JJ, Cawley GC, Villmann T.  2005.  Trends in Neurocomputing at ESANN 2004. Neurocomputing. 64:1–4.
Steil JJ.  In Press.  Roboterlernen ohne Grenzen ? Lernende Roboter und ethische Fragen Christiane Woopen, Marc Jannes [Hrsg.] Roboter in der Gesellschaft. Technische Möglichkeiten und menschliche Verantwortung.
Steil JJ.  2002.  Local structural stability of recurrent networks with time-varying weights. Neurocomputing. 48:39–51.
Steil JJ.  2011.  What do humanoid robots offer to experimental psychology ? Connectionist models of neurocognition and emergent behavior : from theory to applications ; proceedings of the 12th Neural Computation and Psychology Workshop, Birkbeck, University of London, 8 - 10 April 2010. 20:361–371.
Steil JJ, Ritter H.  1999.  Maximisation of stability ranges for recurrent neural networks subject to on-line adaptation. Proc. European Symposium Artificial Neural Networks. :369–374.
Steil JJ.  2005.  Stability of backpropagtion-decorrelation efficient O(N) recurrent learning. Proc. European Symposium Artificial Neural Networks. :43–48.
Steil JJ.  2005.  Memory in Backpropagation-Decorrelation O(N) Efficient Online Recurrent Learning. LNCS. 3697:649–654.
Steil JJ.  2004.  Neural Dynamics for Task-Oriented Grouping of Communicating Agents. Proc. European Symposium Artificial Neural Networks. :531–536.
Steil JJ, Ritter H.  1999.  Recurrent Learning of Input-Output Stable Behaviour in Function Space: A Case Study with the Roessler Attractor. Proc. Int. Conf. Artificial Neural Networks. :761–766.