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Parameterised actions in reinforcement learning are composed of discrete actions with continuous action-parameters.
Robocup: A challenge problem for AI
Hiroaki Kitano, Minoru Asada, Yasuo Kuniyoshi, Itsuki Noda, Eiichi Osawa, and Hitoshi Matsubara · 1997
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Reinforcement Learning: An Introduction
Richard S. Sutton and Andrew G. Barto · 1998
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Jan Peters and Stefan Schaal · 2008
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Value function approximation in reinforcement learning using the Fourier basis
George D. Konidaris, Sarah Osentoski, and Philip S. Thomas · 2011
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Adaptive step-size for online temporal difference learning
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Delving deep into rectifiers: surpassing human-level performance on ImageNet classification
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Human-level control through deep reinforcement learning
Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Andrei A Rusu, Joel Veness, Marc G Bellemare, Alex Graves, Martin Riedmiller, Andreas K Fidjeland, Georg Ostrovski, et al · 2015
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Trust region policy optimization
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Reinforcement learning with parameterized actions
Active exploration and parameterized reinforcement learning applied to a simulated human-robot interaction task
Mehdi Khamassi, George Velentzas, Theodore Tsitsimis, and Costas Tzafestas · 2017
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Hierarchical reinforcement learning with parameters
Maciej Klimek, Henryk Michalewski, and Piotr Miłoś · 2017
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Automatic differentiation in PyTorch
Adam Paszke, Sam Gross, Soumith Chintala, Gregory Chanan, Edward Yang, Zachary DeVito, Zeming Lin, Alban Desmaison, Luca Antiga, and Adam Lerer · 2017
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Ahmed Hussein, Eyad Elyan, and Chrisina Jayne · 2018
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