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A Perceived Environment Design using a Multi-Modal Variational Autoencoder for learning Active-Sensing
This contribution comprises the interplay between a multi-modal variatio...
11/01/2019 ∙ by Timo Korthals, et al. ∙
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From Crystallized Adaptivity to Fluid Adaptivity in Deep Reinforcement Learning -- Insights from Biological Systems on Adaptive Flexibility
Recent developments in machine-learning algorithms have led to impressiv...
08/13/2019 ∙ by Malte Schilling, et al. ∙
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Setup of a Recurrent Neural Network as a Body Model for Solving Inverse and Forward Kinematics as well as Dynamics for a Redundant Manipulator
An internal model of the own body can be assumed a fundamental and evolu...
04/12/2019 ∙ by Malte Schilling, et al. ∙
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Modularization of End-to-End Learning: Case Study in Arcade Games
Complex environments and tasks pose a difficult problem for holistic end...
01/27/2019 ∙ by Andrew Melnik, et al. ∙
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Learning to Run challenge solutions: Adapting reinforcement learning methods for neuromusculoskeletal environments
In the NIPS 2017 Learning to Run challenge, participants were tasked wit...
04/02/2018 ∙ by Łukasz Kidziński, et al. ∙
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