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Novel plasticity rule can explain the development of sensorimotor intelligence.

, and . Proc. Natl. Acad. Sci. U.S.A., 112 (45): E6224-E6232 (2015)

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Daniel Georg University of Stuttgart

Execution Patterns for Quantum Applications, , , , , , , and . Proceedings of the 18th International Conference on Software Technologies, page 258-268. Setúbal, SciTePress, (2023)

Dr. Ilche Georgievski University of Stuttgart

Software Development Life Cycle for Engineering AI Planning Systems. Proceedings of the 18th International Conference on Software Technologies, page 751-760. Setúbal, SciTePress, (2023)
Software Development Life Cycle for Engineering AI Planning Systems. Proceedings of the 18th International Conference on Software Technologies, page 751-760. Setúbal, SciTePress, (2023)Software Engineering Smart Energy Systems, , and . page 1659-1687. Springer, Cham, (2023)

Univ. -Prof. Dr. -Ing. Georg Rademacher University of Stuttgart

The Future of Optical Communications. Handbook of Radio and Optical Networks Convergence, Springer, Singapore, (2023)
 

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Novel plasticity rule can explain the development of sensorimotor intelligence., and . Proc. Natl. Acad. Sci. U.S.A., 112 (45): E6224-E6232 (2015)Linear combination of one-step predictive information with an external reward in an episodic policy gradient setting: a critical analysis., , and . CoRR, (2013)Nonlinear decoding of a complex movie from the mammalian retina., , , , and . PLoS Computational Biology, (2018)Rocking Stamper and Jumping Snakes from a Dynamical Systems Approach to Artificial Life., , and . Adaptive Behaviour, 14 (2): 105-115 (2006)Machine Learning for Haptics: Inferring Multi-Contact Stimulation From Sparse Sensor Configuration., and . Front. Neurorobot., (2019)Variational Autoencoders Pursue PCA Directions (by Accident)., , and . CVPR, page 12406-12415. Computer Vision Foundation / IEEE, (2019)Emergence of natural and robust bipedal walking by learning from biologically plausible objectives, , , , , , and . iScience, (2025)Learning with Muscles : Benefits for Data-Efficiency and Robustness in Anthropomorphic Tasks, , , , , and . Proceedings of The 6th Conference on Robot Learning, 205, page 1178-1188. MLResearchPress, (2022)Variational Autoencoders Pursue PCA Directions (by Accident)., , and . CoRR, (2018)The world as its own best controller: a case study with anthropomimetic robots., and . CoRR, (2016)