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Policy Search for Motor Primitives in Robotics [PDF]
Machine Learning, 2010 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Jens Kober, Jan Peters 0001
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Multi-task policy search for robotics [PDF]
2014 IEEE International Conference on Robotics and Automation (ICRA), 2014 Learning policies that generalize across multiple tasks is an important and challenging research topic in reinforcement learning and robotics. Training individual policies for every single potential task is often impractical, especially for continuous task variations, requiring more principled approaches to share and transfer knowledge among similar ...
Deisenroth, M. +3 more
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Journal of Public Health Research, 2022 Background Pregnancy and postpartum periods represent critical times to support nutrition and household food security, especially for families with limited or strained economic resources.
Dan Ferris +9 more
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Proximal Policy Optimization for Radiation Source Search
Journal of Nuclear Engineering, 2021 Rapid search and localization for nuclear sources can be an important aspect in preventing human harm from illicit material in dirty bombs or from contamination. In the case of a single mobile radiation detector, there are numerous challenges to overcome
Philippe Proctor +3 more
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Learning Replanning Policies With Direct Policy Search [PDF]
IEEE Robotics and Automation Letters, 2019 Direct policy search has been successful in learning challenging real-world robotic motor skills by learning open-loop movement primitives with high sample efficiency. These primitives can be generalized to different contexts with varying initial configurations and goals.
Florian Brandherm +3 more
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Exemplar-Based Direct Policy Search with Evolutionary Optimization [PDF]
, 2005 In this paper, an exemplar-based policy optimization framework for direct policy search is presented. In this exemplar-based approach, the policy to be optimized is composed of a set of exemplars and a case-based action selector.
IKEDA, Kokolo
core +1 more source
Learning Trajectory Distributions for Assisted Teleoperation and Path Planning
Frontiers in Robotics and AI, 2019 Several approaches have been proposed to assist humans in co-manipulation and teleoperation tasks given demonstrated trajectories. However, these approaches are not applicable when the demonstrations are suboptimal or when the generalization capabilities
Marco Ewerton +9 more
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Quantum architecture search via truly proximal policy optimization
Scientific Reports, 2023 Quantum Architecture Search (QAS) is a process of voluntarily designing quantum circuit architectures using intelligent algorithms. Recently, Kuo et al. (Quantum architecture search via deep reinforcement learning.
Xianchao Zhu, Xiaokai Hou
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Improving the Effectiveness and Efficiency of Web-Based Search Tasks for Policy Workers
Information, 2023 We adapt previous literature on search tasks for developing a domain-specific search engine that supports the search tasks of policy workers. To characterise the search tasks we conducted two rounds of interviews with policy workers at the municipality ...
Thomas Schoegje +3 more
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Assisting Movement Training and Execution With Visual and Haptic Feedback
Frontiers in Neurorobotics, 2018 In the practice of motor skills in general, errors in the execution of movements may go unnoticed when a human instructor is not available. In this case, a computer system or robotic device able to detect movement errors and propose corrections would be ...
Marco Ewerton +8 more
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