Fetching the paper…
Reading the bibliography…
Rapid progress in deep reinforcement learning has made it increasingly feasible to train controllers for high-dimensional humanoid bodies.
Leonardo’s Lost Robots
Mark Rosheim · 2006
Earlier work this paper cites.
Modeling human motion using binary latent variables
Graham W Taylor, Geoffrey E Hinton, and Sam T Roweis · 2007
Earlier work this paper cites.
Generating coherent patterns of activity from chaotic neural networks
David Sussillo and Larry F Abbott · 2009
Earlier work this paper cites.
Robust physics-based locomotion using low-dimensional planning
Igor Mordatch, Martin De Lasa, and Aaron Hertzmann · 2010
Earlier work this paper cites.
Sampling-based contact-rich motion control
Libin Liu, KangKang Yin, Michiel van de Panne, Tianjia Shao, and Weiwei Xu · 2010
Earlier work this paper cites.
Locomotion skills for simulated quadrupeds
Stelian Coros, Andrej Karpathy, Ben Jones, Lionel Reveret, and Michiel Van De Panne · 2011
Earlier work this paper cites.
Mujoco: A physics engine for model-based control
Emanuel Todorov, Tom Erez, and Yuval Tassa · 2012
Earlier work this paper cites.
Terrain runner: control, parameterization, composition, and planning for highly dynamic motions
Libin Liu, KangKang Yin, Michiel van de Panne, and Baining Guo · 2012
Cited alongside, same era.
Data-driven control of flapping flight
Eunjung Ju, Jungdam Won, Jehee Lee, Byungkuk Choi, Junyong Noh, and Min Gyu Choi · 2013
Cited alongside, same era.
Trajectory optimization for full-body movements with complex contacts
Mazen Al Borno, Martin De Lasa, and Aaron Hertzmann · 2013
Cited alongside, same era.
Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
Cited alongside, same era.
Conceptors: an easy introduction
Herbert Jaeger · 2014
Cited alongside, same era.
Online motion synthesis using sequential monte carlo
Generative adversarial imitation learning
Jonathan Ho and Stefano Ermon · 2016
Later among the works it cites.
Learning and transfer of modulated locomotor controllers
Nicolas Heess, Greg Wayne, Yuval Tassa, Timothy Lillicrap, Martin Riedmiller, and David Silver · 2016
Later among the works it cites.
Task-based locomotion
Shailen Agrawal and Michiel van de Panne · 2016
Later among the works it cites.
Terrain-adaptive locomotion skills using deep reinforcement learning
Xue Bin Peng, Glen Berseth, and Michiel van de Panne · 2016
Later among the works it cites.
Deeploco: Dynamic locomotion skills using hierarchical deep reinforcement learning
Xue Bin Peng, Glen Berseth, KangKang Yin, and Michiel van de Panne · 2017
Closest in time.
Phase-functioned neural networks for character control
Daniel Holden, Taku Komura, and Jun Saito · 2017
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Perttu Hämäläinen, Sebastian Eriksson, Esa Tanskanen, Ville Kyrki, and Jaakko Lehtinen · 2014
Cited alongside, same era.
Interactive control of diverse complex characters with neural networks
Igor Mordatch, Kendall Lowrey, Galen Andrew, Zoran Popovic, and Emanuel V Todorov · 2015
Cited alongside, same era.
Trust region policy optimization
John Schulman, Sergey Levine, Pieter Abbeel, Michael I Jordan, and Philipp Moritz
Cited in the paper.
High-dimensional continuous control using generalized advantage estimation
John Schulman, Philipp Moritz, Sergey Levine, Michael Jordan, and Pieter Abbeel
Cited in the paper.
Closest in time.