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Action representations in robotics: A taxonomy and systematic classification.

, , , , and . Int. J. Robotics Res., (2019)

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ROSSINI: RobOt kidS deSIgn thiNkIng., , , , , , , and . RiE, volume 1316 of Advances in Intelligent Systems and Computing, page 16-25. Springer, (2020)Action representations in robotics: A taxonomy and systematic classification., , , , and . Int. J. Robotics Res., (2019)Improving the Exploration of Deep Reinforcement Learning in Continuous Domains using Planning for Policy Search., , , and . CoRR, (2020)Deep Learning for Fast Segmentation of E-waste Devices' Inner Parts in a Recycling Scenario., , and . ICPRAI (1), volume 13363 of Lecture Notes in Computer Science, page 161-172. Springer, (2022)Editorial: Computational models of affordance for robotics., , , and . Frontiers Neurorobotics, (September 2022)Action Noise in Off-Policy Deep Reinforcement Learning: Impact on Exploration and Performance., , , , and . CoRR, (2022)Coping with the variability in humans reward during simulated human-robot interactions through the coordination of multiple learning strategies., , , , and . RO-MAN, page 612-617. IEEE, (2020)How do Offline Measures for Exploration in Reinforcement Learning behave?, , , , and . CoRR, (2020)Reducing Computational Cost During Robot Navigation and Human-Robot Interaction with a Human-Inspired Reinforcement Learning Architecture., , , , , , and . Int. J. Soc. Robotics, 15 (8): 1297-1323 (August 2023)How to Reduce Computation Time While Sparing Performance During Robot Navigation? A Neuro-Inspired Architecture for Autonomous Shifting Between Model-Based and Model-Free Learning., , , , , and . Living Machines, volume 12413 of Lecture Notes in Computer Science, page 68-79. Springer, (2020)