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

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

9 October 2020
Daniele Reda
Tianxin Tao
M. van de Panne
    AI4CE
ArXiv (abs)PDFHTML

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
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
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
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
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
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
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
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
SDGym: Low-Code Reinforcement Learning Environments using System Dynamics Models
Emmanuel Klu
Sameer Sethi
DJ Passey
Donald Martin
AI4CESyDa
82
0
0
19 Oct 2023
Investigating the Impact of Action Representations in Policy Gradient
  Algorithms
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
Observation Space Matters: Benchmark and Optimization Algorithm
J. Kim
Sehoon Ha
OODOffRL
49
11
0
02 Nov 2020
Applicability and Challenges of Deep Reinforcement Learning for
  Satellite Frequency Plan Design
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
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
PFPN: Continuous Control of Physically Simulated Characters using Particle Filtering Policy Network
Pei Xu
Ioannis Karamouzas
12
3
0
16 Mar 2020
1