Deep Reinforcement Learning for the Control of Robotic Manipulation: A Focussed Mini-Review
作者： Michel de Mathelin , Florent Nageotte , Birgitta Dresp-Langley , Rongrong Liu , Philippe Zanne
关键词: Control (management) 、 Human–computer interaction 、 Curse of dimensionality 、 Domain (software engineering) 、 Artificial intelligence 、 Generalization (learning) 、 Deep learning 、 Reinforcement learning 、 Robot 、 Computer science
摘要: … This review paper tries to provide a brief and self-contained review of DRL in the research … We will start with a brief introduction of deep learning, reinforcement learning, and DRL in the …
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sci-hub.st 参考文章(68)
Serge J. Belongie, Benjamin Spector, Sample-Efficient Reinforcement Learning through Transfer and Architectural Priors arXiv: Learning. ,(2018)
Joschka Boedecker, Wolfram Burgard, Ming Liu, Jingwei Zhang, Lei Tai, A Survey of Deep Network Solutions for Learning Control in Robotics: From Reinforcement to Imitation arXiv: Robotics. ,(2016)
Venkata Krishna Prashanth Eranki, Rishank Reddy Gurudu, Design and Structural Analysis of a Robotic Arm ,(2017)
Christian Szegedy, Sergey Ioffe, Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift arXiv: Learning. ,(2015)
Pieter Abbeel, Chelsea Finn, Sergey Levine, Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks arXiv: Learning. ,(2017)
Pieter Abbeel, Sergey Levine, Nolan Wagener, Learning Contact-Rich Manipulation Skills with Guided Policy Search arXiv: Robotics. ,(2015)
Noam Brown, Tuomas Sandholm, Superhuman AI for multiplayer poker Science. ,vol. 365, pp. 885- 890 ,(2019) , 10.1126/SCIENCE.AAY2400
Sergey Levine, Peter Pastor, Alex Krizhevsky, Julian Ibarz, Deirdre Quillen, Learning Hand-Eye Coordination for Robotic Grasping with Deep Learning and Large-Scale Data Collection The International Journal of Robotics Research. ,vol. 37, pp. 421- 436 ,(2018) , 10.1177/0278364917710318
Satinder Singh, Honglak Lee, Junhyuk Oh, Richard Lewis, Xiaoxiao Guo, Action-conditional video prediction using deep networks in Atari games neural information processing systems. ,vol. 28, pp. 2863- 2871 ,(2015)
Anusha Nagabandi, Gregory Kahn, Ronald S. Fearing, Sergey Levine, Neural Network Dynamics for Model-Based Deep Reinforcement Learning with Model-Free Fine-Tuning international conference on robotics and automation. pp. 7559- 7566 ,(2018) , 10.1109/ICRA.2018.8463189