Found 193 results
Author Title [ Type(Desc)] Year
Search results for Steil  [Reset Search]
Conference Paper
Soltoggio A, Lemme A, Steil JJ.  2012.  Using movement primitives in interpreting and decomposing complex trajectories in learning-by-doing. :1427–1433.
Wrede S, Beyer O, Dreyer C, Wojtynek M, Steil JJ.  2016.  Vertical Integration and Service Orchestration for Modular Production Systems using Business Process Models. Procedia Technologica. 26:259–266.
Schiller U.D, Steil JJ.  2003.  On the weight dynamcis of recurrent learning. Proc. European Symposium Artificial Neural Networks. :73–78.
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.
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.
Journal Article
Steil JJ, Götting M, Wersing H, Körner E, Ritter H.  2007.  Adaptive scene dependent filters for segmentation and online learning of visual objects. Neurocomputing. 70:1235–1246.
Liu W, Chen D, Steil JJ.  2017.  Analytical Inverse Kinematics Solver for Anthropomorphic 7-DOF Redundant Manipulators with Human-Like Configuration Constraints. Journal of Intelligent & Robotic Systems. 86(1):63-79.
Schiller UD, Steil JJ.  2005.  Analyzing the weight dynamics of recurrent learning algorithms. Neurocomputing. 63:5–23.
Queißer J, Steil JJ.  2018.  Bootstrapping of Parameterized Skills Through Hybrid Optimization in Task and Policy Spaces. Frontiers in Robotics and AI, section Humanoid Robotics. 5
Wersing H, Steil JJ, Ritter H.  2001.  A Competitive Layer Model for Feature Binding and Sensory Segmentation. Neural Computation. 13:357–387.
Reinhart F, Steil JJ.  2011.  A constrained regularization approach for input-driven recurrent neural networks. Differential Equations and Dynamical Systems. 19:27–46.
He H, Chawla N, Chen H, Choe Y, Engelbrecht A, Deva J, Long L, Minai A, Nie F, Ozertem U et al..  2016.  Editorial IEEE Transactions on Neural Networks and Learning Systems 2016 and Beyond. IEEE Transactions on Neural Networks and Learning Systems. 27:1–7.
Kopp S, Steil J.  2011.  Editorial Special Corner on Cognitive Robotics. Cognitive Processing. 12:317–318.
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.
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.
Rolf M, Steil JJ.  2013.  Explorative learning of right inverse functions: theoretical implications of redundancy. Neurocomputing.
Rolf M, Steil JJ, Gienger M..  2010.  Goal Babbling permits direct learning of inverse kinematics. IEEE Trans. Autonomous Mental Development. 2:216–229.
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.
Steil JJ, Sagerer G, Ritter H, Körner E.  2008.  Humans and Humanoids - Perspectives on Research in Cognition and Robotics. KI - Künstliche Intelligenz. 4:33–36.
Reinhart F, Shareef Z, Steil JJ.  2017.  Hybrid Analytical and Data-driven Modeling for Feed-forward Robot Control. Sensors. 17(2)
Schrauwen B, Wardermann M, Verstraeten D, Steil JJ, Stroobandt D.  2008.  Improving reservoirs using intrinsic plasticity. Neurocomputing. 71:1159–1171.
Haschke R, Steil JJ.  2005.  Input Space Bifurcation Manifolds of Recurrent Neural Networks. Neurocomputing. 64:25–38.
Steffen JFrederik, Pardowitz M, Steil JJ, Ritter H.  2011.  Integrating Feature Maps and Competitive Layer Architectures For Motion Segmentation. Neurocomputing. 74:1372–1381.
Muehlig M, Steil JJ, Gienger M..  2012.  Interactive Imitation Learning of Object Movement Skills. Autonomous Robots. 32:97–114.
Neumann K, Strub C, Steil JJ.  2013.  Intrinsic Plasticity via Natural Gradient Descent with Application to Drift Compensation. Neurocomputing. 112:26–33.