Learning to Locomote: Understanding How Environment Design Matters for Deep Reinforcement Learning

9 October 2020

Papers citing "Learning to Locomote: Understanding How Environment Design Matters for Deep Reinforcement Learning"

30 / 30 papers shown

Title
A General Approach of Automated Environment Design for Learning the Optimal Power Flow Thomas Wolgast Astrid Nieße AI4CE 65 0 0 01 May 2025
How to Choose a Reinforcement-Learning Algorithm Fabian Bongratz Vladimir Golkov Lukas Mautner Luca Della Libera Frederik Heetmeyer Felix Czaja Julian Rodemann Daniel Cremers 68 1 0 30 Jul 2024
Actuators À La Mode: Modal Actuations for Soft Body Locomotion Otman Benchekroun Kaixiang Xie Hsueh-Ti Derek Liu E. Grinspun Sheldon Andrews Victor Zordan AI4CE 104 1 0 28 May 2024
Attaining Human`s Desirable Outcomes in Human-AI Interaction via Structural Causal Games Anjie Liu Jianhong Wang Haoxuan Li Xu Chen Jun Wang Samuel Kaski Mengyue Yang 84 0 0 26 May 2024
Learning the Optimal Power Flow: Environment Design Matters Thomas Wolgast Astrid Nieße AI4CE 56 6 0 26 Mar 2024
Attention-based Reinforcement Learning for Combinatorial Optimization: Application to Job Shop Scheduling Problem Jaejin Lee Seho Kee Mani Janakiram George Runger OffRL 55 3 0 29 Jan 2024
Information-Theoretic State Variable Selection for Reinforcement Learning Charles Westphal Stephen Hailes Mirco Musolesi 76 3 0 21 Jan 2024
SDGym: Low-Code Reinforcement Learning Environments using System Dynamics Models Emmanuel Klu Sameer Sethi DJ Passey Donald Martin AI4CE SyDa 82 0 0 19 Oct 2023
Investigating the Impact of Action Representations in Policy Gradient Algorithms Jan Schneider-Barnes Pierre Schumacher Daniel Haeufle Bernhard Scholkopf Le Chen OffRL 41 2 0 13 Sep 2023
Physics-based Motion Retargeting from Sparse Inputs Daniele Reda Jungdam Won Yuting Ye M. van de Panne Alexander Winkler VGen 67 12 0 04 Jul 2023
Identifying Important Sensory Feedback for Learning Locomotion Skills Wanming Yu Chuanyu Yang C. McGreavy Eleftherios Triantafyllidis Guillaume Bellegarda M. Shafiee A. Ijspeert Zhibin Li 83 16 0 29 Jun 2023
Progress and summary of reinforcement learning on energy management of MPS-EV Jincheng Hu Yang Lin Liang Chu Zhuoran Hou Jihan Li Jingjing Jiang Yuanjian Zhang 130 13 0 08 Nov 2022
The Impact of Task Underspecification in Evaluating Deep Reinforcement Learning Vindula Jayawardana Catherine Tang Sirui Li Da Suo Cathy Wu OffRL 108 13 0 16 Oct 2022
Design of experiments for the calibration of history-dependent models via deep reinforcement learning and an enhanced Kalman filter Ruben Villarreal Nikolaos N. Vlassis Nhon N. Phan Tommie A. Catanach Reese E. Jones N. Trask S. Kramer WaiChing Sun OffRL 59 12 0 27 Sep 2022
Understanding reinforcement learned crowds Ariel Kwiatkowski Vicky Kalogeiton Julien Pettré Marie-Paule Cani 53 10 0 19 Sep 2022
Learning with Muscles: Benefits for Data-Efficiency and Robustness in Anthropomorphic Tasks Isabell Wochner Pierre Schumacher Georg Martius Le Chen Syn Schmitt Daniel Haeufle 82 9 0 08 Jul 2022
Critic Sequential Monte Carlo Vasileios Lioutas J. Lavington Justice Sefas Matthew Niedoba Yunpeng Liu Berend Zwartsenberg Setareh Dabiri Frank Wood Adam Scibior 105 7 0 30 May 2022
Learning Torque Control for Quadrupedal Locomotion Shuxiao Chen Bike Zhang M. Mueller Akshara Rai Koushil Sreenath 90 39 0 10 Mar 2022
A Survey on Reinforcement Learning Methods in Character Animation Ariel Kwiatkowski Eduardo Alvarado Vicky Kalogeiton Chenxi Liu Julien Pettré M. van de Panne Marie-Paule Cani AI4CE 97 46 0 07 Mar 2022
Concurrent Training of a Control Policy and a State Estimator for Dynamic and Robust Legged Locomotion Gwanghyeon Ji Juhyeok Mun Hyeongjun Kim Jemin Hwangbo 85 148 0 11 Feb 2022
Detecting danger in gridworlds using Gromov's Link Condition Thomas F Burns R. Tang AI4CE 74 2 0 17 Jan 2022
Reinforcement Learning with Adaptive Curriculum Dynamics Randomization for Fault-Tolerant Robot Control W. Okamoto Hiroshi Kera K. Kawamoto 125 8 0 19 Nov 2021
Braxlines: Fast and Interactive Toolkit for RL-driven Behavior Engineering beyond Reward Maximization S. Gu Manfred Diaz Daniel Freeman Hiroki Furuta Seyed Kamyar Seyed Ghasemipour Anton Raichuk Byron David Erik Frey Erwin Coumans Olivier Bachem 80 14 0 10 Oct 2021
Accessibility-Based Clustering for Efficient Learning of Locomotion Skills Chong Zhang Wanming Yu Zhibin Li 116 10 0 23 Sep 2021
Reinforcement Learning with Formal Performance Metrics for Quadcopter Attitude Control under Non-nominal Contexts Nicola Bernini M. Bessa R. Delmas A. Gold Eric Goubault R. Pennec S. Putot Franccois Sillion 49 7 0 27 Jul 2021
Towards Automatic Actor-Critic Solutions to Continuous Control J. E. Grigsby Jinsu Yoo Yanjun Qi OffRL 78 6 0 16 Jun 2021
Observation Space Matters: Benchmark and Optimization Algorithm J. Kim Sehoon Ha OOD OffRL 49 11 0 02 Nov 2020
Applicability and Challenges of Deep Reinforcement Learning for Satellite Frequency Plan Design J. Luis E. Crawley B. Cameron 51 6 0 15 Oct 2020
Understanding the Stability of Deep Control Policies for Biped Locomotion Hwangpil Park R. Yu Yoonsang Lee Kyungho Lee Jehee Lee 52 9 0 30 Jul 2020
PFPN: Continuous Control of Physically Simulated Characters using Particle Filtering Policy Network Pei Xu Ioannis Karamouzas 12 3 0 16 Mar 2020