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Learning motor skills for robots is a hard task. In particular, a high number of degrees-of-freedom in the robot can pose serious challenges to existing reinforcement learning methods, since it leads to a high-dimensional search space. However, complex robots are often intrinsically redundant systems and, therefore, can be controlled using a latent manifold of much smaller dimensionality. In this...
Living organisms are characterized by their smooth adaptability to environmental changes and their robustness against morphological modifications. To investigate the computational mechanisms behind such learning scheme, we proposed tacit learning as a novel learning method. In tacit learning, there are no clear distinctions between learning and motor control: learning is a simple accumulation process...
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