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A Framework for Studying Reinforcement Learning and Sim-to-Real in Robot
  Soccer

A Framework for Studying Reinforcement Learning and Sim-to-Real in Robot Soccer

18 August 2020
H. Bassani
R. A. Delgado
J. N. D. O. L. Junior
H. R. Medeiros
Pedro H. M. Braga
Mateus G. Machado
L. H. C. Santos
Alain Tapp
ArXivPDFHTML

Papers citing "A Framework for Studying Reinforcement Learning and Sim-to-Real in Robot Soccer"

15 / 15 papers shown
Title
Google Research Football: A Novel Reinforcement Learning Environment
Google Research Football: A Novel Reinforcement Learning Environment
Karol Kurach
Anton Raichuk
Piotr Stańczyk
Michal Zajac
Olivier Bachem
...
C. Riquelme
Damien Vincent
Marcin Michalski
Olivier Bousquet
Sylvain Gelly
123
400
0
25 Jul 2019
Challenges of Real-World Reinforcement Learning
Challenges of Real-World Reinforcement Learning
Gabriel Dulac-Arnold
D. Mankowitz
Todd Hester
OffRL
69
545
0
29 Apr 2019
Soft Actor-Critic Algorithms and Applications
Soft Actor-Critic Algorithms and Applications
Tuomas Haarnoja
Aurick Zhou
Kristian Hartikainen
George Tucker
Sehoon Ha
...
Vikash Kumar
Henry Zhu
Abhishek Gupta
Pieter Abbeel
Sergey Levine
105
2,391
0
13 Dec 2018
Closing the Sim-to-Real Loop: Adapting Simulation Randomization with
  Real World Experience
Closing the Sim-to-Real Loop: Adapting Simulation Randomization with Real World Experience
Yevgen Chebotar
Ankur Handa
Viktor Makoviychuk
Miles Macklin
J. Issac
Nathan D. Ratliff
Dieter Fox
61
503
0
12 Oct 2018
Learning Dexterous In-Hand Manipulation
Learning Dexterous In-Hand Manipulation
OpenAI OpenAI
Marcin Andrychowicz
Bowen Baker
Maciek Chociej
Rafal Jozefowicz
...
Szymon Sidor
Joshua Tobin
Peter Welinder
Lilian Weng
Wojciech Zaremba
78
1,865
0
01 Aug 2018
AutoAugment: Learning Augmentation Policies from Data
AutoAugment: Learning Augmentation Policies from Data
E. D. Cubuk
Barret Zoph
Dandelion Mané
Vijay Vasudevan
Quoc V. Le
98
1,764
0
24 May 2018
DARLA: Improving Zero-Shot Transfer in Reinforcement Learning
DARLA: Improving Zero-Shot Transfer in Reinforcement Learning
I. Higgins
Arka Pal
Andrei A. Rusu
Loic Matthey
Christopher P. Burgess
Alexander Pritzel
M. Botvinick
Charles Blundell
Alexander Lerchner
DRL
97
413
0
26 Jul 2017
Proximal Policy Optimization Algorithms
Proximal Policy Optimization Algorithms
John Schulman
Filip Wolski
Prafulla Dhariwal
Alec Radford
Oleg Klimov
OffRL
236
18,685
0
20 Jul 2017
Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments
Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments
Ryan J. Lowe
Yi Wu
Aviv Tamar
J. Harb
Pieter Abbeel
Igor Mordatch
116
4,441
0
07 Jun 2017
Transfer from Simulation to Real World through Learning Deep Inverse
  Dynamics Model
Transfer from Simulation to Real World through Learning Deep Inverse Dynamics Model
Paul Christiano
Zain Shah
Igor Mordatch
Jonas Schneider
T. Blackwell
Joshua Tobin
Pieter Abbeel
Wojciech Zaremba
PINN
48
249
0
11 Oct 2016
OpenAI Gym
OpenAI Gym
Greg Brockman
Vicki Cheung
Ludwig Pettersson
Jonas Schneider
John Schulman
Jie Tang
Wojciech Zaremba
OffRL
ODL
174
5,056
0
05 Jun 2016
Continuous control with deep reinforcement learning
Continuous control with deep reinforcement learning
Timothy Lillicrap
Jonathan J. Hunt
Alexander Pritzel
N. Heess
Tom Erez
Yuval Tassa
David Silver
Daan Wierstra
193
13,174
0
09 Sep 2015
End-to-End Training of Deep Visuomotor Policies
End-to-End Training of Deep Visuomotor Policies
Sergey Levine
Chelsea Finn
Trevor Darrell
Pieter Abbeel
BDL
228
3,418
0
02 Apr 2015
Trust Region Policy Optimization
Trust Region Policy Optimization
John Schulman
Sergey Levine
Philipp Moritz
Michael I. Jordan
Pieter Abbeel
245
6,722
0
19 Feb 2015
Playing Atari with Deep Reinforcement Learning
Playing Atari with Deep Reinforcement Learning
Volodymyr Mnih
Koray Kavukcuoglu
David Silver
Alex Graves
Ioannis Antonoglou
Daan Wierstra
Martin Riedmiller
103
12,163
0
19 Dec 2013
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