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Neumann G. Variational Inference for Policy Search in Changing Situations. In: Getoor L, Scheffer T Proceedings of the 28th International Conference on Machine Learning (ICML-11). Proceedings of the 28th International Conference on Machine Learning (ICML-11). New York, NY, USA: ACM; 2011. pp. 817–824. Available from: http://www.igi.tugraz.at/gerhard/research/papers/441_icmlNeumann.pdf
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Rückert EA, Neumann G, Toussaint M, Maass W. Learned graphical models for probabilistic planning provide a new class of movement primitives. Frontiers in Computational Neuroscience (Special Issue on Modularity in motor control: from muscle synergies to cognitive action representation) [Internet]. 2013 ;6. Available from: http://www.frontiersin.org/computational_neuroscience/10.3389/fncom.2012.00097/abstract
Rückert EA, d'Avella A. Learned Muscle Synergies as Prior in Dynamical Systems for Controlling Bio-mechanical and Robotic Systems. In: Abstracts of Neural Control of Movement Conference (NCM 2013). Abstracts of Neural Control of Movement Conference (NCM 2013). ; 2013. Available from: http://eprints.pascal-network.org/archive/00009898/
Rückert E, d'Avella A. Learned parametrized dynamic movement primitives with shared synergies for controlling robotic and musculoskeletal systems. Frontiers in Computational Neuroscience (Special Issue on Modularity in motor control: from muscle synergies to cognitive action representation) [Internet]. 2013 ;7:138. Available from: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3797962/
Rückert EA, Neumann G. Stochastic Optimal Control Methods for Investigating the Power of Morphological Computation. Artificial Life (Special Issue on Morphological Computation) [Internet]. 2012 ;19:115–131. Available from: http://www.ias.informatik.tu-darmstadt.de/uploads/Site/EditPublication/r%fcckert2012_artificiallife.pdf
Rückert EA, Neumann G. A study of Morphological Computation by using Probabilistic Inference for Motor Planning. In: 2nd International Conference on Morphological Computation (ICMC2011). 2nd International Conference on Morphological Computation (ICMC2011). Venice, Italy; 2011. pp. 51–53. Available from: http://eprints.pascal-network.org/archive/00008757/01/AICOMorphComp.pdf

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