Biblio
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2017.
Learning Inverse Kinematics for Pose-Constraint Bi-Manual Movements. From Animals to Animats 11. 11th International Conference on Simulation of Adaptive Behavior, SAB 2010. Proceedings. 6226
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2015. .
2018. Learning Flexible Full Body Kinematics for Humanoid Tool Use. Int. Symp. Learning and Adaptive Behavior in Robotic Systems (Best Paper Award). :171–176.
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2010. Learning Compatibitlity Functions for Feature Binding and Perceptual Grouping. Proc. of Int. Conference Artificial Neural Networks. LNCS 2714:60–67.
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2003. A Layered Recurrent Neural Network for Feature Grouping. Int. Conf. on Artificial Neural Networks. :439–444.
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1997. .
2020.
"Können Maschinen Ethisches Verhalten Lernen ?" Bericht zum 1. SYnENZ Zirkel der BWG Kommission für Synergie und Intelligenz (SYnENZ) Jahrbuch der Braunschweigischen Wissenschaftlichen Gesellschaft. :117-120.
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2021. Kollaborative Roboter – universale Werkzeuge in der digitalisierten und vernetzten Arbeitswelt. G. W. Maier, G. Engels, E. Steffen (Hrg.): Handbuch Gestaltung digitaler und vernetzter Arbeitswelten. :323-346.
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2020. Kinesthetic Teaching Using Assisted Gravity Compensation for Model-Free Trajectory Generation in Confined Spaces. Gearing Up and Accelerating Cross-Fertilization between Academic and Industrial Robotics Research in Europe. 94:107–127.
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2013. Kinesthetic teaching of visuomotor coordination for pointing by the humanoid robot iCub. Neurocomputing. 112:179–188.
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2013. KI für die Fachkräftesicherung nutzen. Lösungsansätze für Automatisierung, Teilhabe und Wissenstransfer.. Whitepaper aus der Plattform Lernende Systeme.
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2024. Ist KI zu kontrollieren? Überlegungen zur Ethik des Zusammenwirkens von Menschen und KI-Maschinen In Steil, J.J. et al. Hrsg.: SYnENZ - Synergie und Intelligenz im Zusammenwirken von Mensch und Maschine: Beurteilen - Messen - Bewerten.
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In Press. Intrinsic Plasticity via Natural Gradient Descent with Application to Drift Compensation. Neurocomputing. 112:26–33.
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2013. Intrinsic Plasticity via Natural Gradient Decent. 20th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2012). Proceedings. :555–560.
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2012. Interest-Driven Exploration with Observational Learning for Developmental Robots. IEEE Transactions on Cognitive and Developmental Systems .
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2021. .
2021. Interactive Learning of Inverse Kinematics with Nullspace Constraints using Recurrent Neural Networks. Proc. 20. Workshop on Computational Intelligence.
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2010. .
2012. Interactive Imitation Learning of Object Movement Skills. Autonomous Robots. 32:97–114.
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2012. .
2012. Integrating Inhomogeneous Processing and Proto-object Formation in a Computational Model of Visual Attention. Human Centered Robot Systems: Cognition, Interaction, Technology. :93–102.
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2009. Integrating Feature Maps and Competitive Layer Architectures For Motion Segmentation. Neurocomputing. 74:1372–1381.
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2011. Input-Output Stability of Recurrent Neural Networks with Delays using Circle Criteria. Proc. Int. ICSC/IFAC Symposium on Neural Computation. :519–525.
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1998.