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Learning locomotion skills is a challenging problem.
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A Short Tutorial on Multibody Dynamics
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Source task creation for curriculum learning. In Proceedings of the 2016 International Conference on Autonomous Agents & Multiagent Systems
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Terrain-adaptive Locomotion Skills Using Deep Reinforcement Learning
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Supersizing self-supervision: Learning to grasp from 50k tries and 700 robot hours. In Robotics and Automation (ICRA), 2016 IEEE International Conference on
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OpenAI Baselines
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Alex Graves, Marc G Bellemare, Jacob Menick, Remi Munos, and Koray Kavukcuoglu. 2017 · 2017
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Emergence of locomotion behaviours in rich environments
Nicolas Heess, Srinivasan Sriram, Jay Lemmon, Josh Merel, Greg Wayne, Yuval Tassa, Tom Erez, Ziyu Wang, Ali Eslami, Martin Riedmiller, et al · 2017
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Learning to schedule control fragments for physics-based characters using deep q-learning
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Teacher-Student Curriculum Learning
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openai/roboschool
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DeepLoco: Dynamic Locomotion Skills Using Hierarchical Deep Reinforcement Learning
Xue Bin Peng, Glen Berseth, Kangkang Yin, and Michiel Van De Panne. 2017 · 2017
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Proximal policy optimization algorithms
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov. 2017 · 2017
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How to train your dragon: example-guided control of flapping flight
Jungdam Won, Jongho Park, Kwanyu Kim, and Jehee Lee. 2017 · 2017
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