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2006.05990
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What Matters In On-Policy Reinforcement Learning? A Large-Scale Empirical Study
10 June 2020
Marcin Andrychowicz
Anton Raichuk
Piotr Stańczyk
Manu Orsini
Sertan Girgin
Raphaël Marinier
Léonard Hussenot
Matthieu Geist
Olivier Pietquin
Marcin Michalski
Sylvain Gelly
Olivier Bachem
OffRL
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Papers citing
"What Matters In On-Policy Reinforcement Learning? A Large-Scale Empirical Study"
36 / 136 papers shown
A Safety-Critical Decision Making and Control Framework Combining Machine Learning and Rule-based Algorithms
Andrei Aksjonov
Ville Kyrki
112
5
0
30 Jan 2022
The Effects of Reward Misspecification: Mapping and Mitigating Misaligned Models
International Conference on Learning Representations (ICLR), 2022
Alexander Pan
Kush S. Bhatia
Jacob Steinhardt
396
249
0
10 Jan 2022
Distilled Domain Randomization
J. Brosseit
Benedikt Hahner
Fabio Muratore
Michael Gienger
Jan Peters
161
4
0
06 Dec 2021
Residual Pathway Priors for Soft Equivariance Constraints
Marc Finzi
Gregory W. Benton
A. Wilson
BDL
UQCV
215
75
0
02 Dec 2021
Continuous Control With Ensemble Deep Deterministic Policy Gradients
Piotr Januszewski
Mateusz Olko
M. Królikowski
J. Swiatkowski
Marcin Andrychowicz
Lukasz Kuciñski
Piotr Milo's
OffRL
127
12
0
30 Nov 2021
Learning Representations for Pixel-based Control: What Matters and Why?
Manan Tomar
Utkarsh Aashu Mishra
Amy Zhang
Matthew E. Taylor
SSL
OffRL
236
31
0
15 Nov 2021
Investigation of Independent Reinforcement Learning Algorithms in Multi-Agent Environments
Frontiers in Artificial Intelligence (Front. Artif. Intell.), 2021
Ken Ming Lee
Sriram Ganapathi Subramanian
Mark Crowley
100
19
0
01 Nov 2021
MEPG: A Minimalist Ensemble Policy Gradient Framework for Deep Reinforcement Learning
Qiang He
Yuxun Qu
Chen Gong
Xinwen Hou
OffRL
181
10
0
22 Sep 2021
A Continuous Optimisation Benchmark Suite from Neural Network Regression
K. Malan
C. Cleghorn
ODL
93
2
0
12 Sep 2021
MimicBot: Combining Imitation and Reinforcement Learning to win in Bot Bowl
Nicola Pezzotti
153
1
0
21 Aug 2021
What Matters in Learning from Offline Human Demonstrations for Robot Manipulation
Conference on Robot Learning (CoRL), 2021
Ajay Mandlekar
Danfei Xu
J. Wong
Soroush Nasiriany
Chen Wang
Rohun Kulkarni
Li Fei-Fei
Silvio Savarese
Yuke Zhu
Roberto Martín-Martín
OffRL
525
709
0
06 Aug 2021
A Pragmatic Look at Deep Imitation Learning
Kai Arulkumaran
D. Lillrank
266
11
0
04 Aug 2021
On-Policy Deep Reinforcement Learning for the Average-Reward Criterion
International Conference on Machine Learning (ICML), 2021
Yiming Zhang
George Andriopoulos
OffRL
222
53
0
14 Jun 2021
Correcting Momentum in Temporal Difference Learning
Emmanuel Bengio
Joelle Pineau
Doina Precup
156
11
0
07 Jun 2021
Average-Reward Reinforcement Learning with Trust Region Methods
International Joint Conference on Artificial Intelligence (IJCAI), 2021
Xiaoteng Ma
Xiao-Jing Tang
Li Xia
Jun Yang
Qianchuan Zhao
224
23
0
07 Jun 2021
Towards Deeper Deep Reinforcement Learning with Spectral Normalization
Neural Information Processing Systems (NeurIPS), 2021
Johan Bjorck
Daniel Schwalbe-Koda
Kilian Q. Weinberger
322
25
0
02 Jun 2021
What Matters for Adversarial Imitation Learning?
Neural Information Processing Systems (NeurIPS), 2021
Manu Orsini
Anton Raichuk
Léonard Hussenot
Damien Vincent
Robert Dadashi
Sertan Girgin
Matthieu Geist
Olivier Bachem
Olivier Pietquin
Marcin Andrychowicz
229
88
0
01 Jun 2021
Hyperparameter Selection for Imitation Learning
International Conference on Machine Learning (ICML), 2021
Léonard Hussenot
Marcin Andrychowicz
Damien Vincent
Robert Dadashi
Anton Raichuk
...
Sabela Ramos
Manu Orsini
Olivier Bachem
Matthieu Geist
Olivier Pietquin
251
19
0
25 May 2021
The Fragility of Noise Estimation in Kalman Filter: Optimization Can Handle Model-Misspecification
Ido Greenberg
Shie Mannor
Netanel Yannay
259
4
0
06 Apr 2021
Decoupling Value and Policy for Generalization in Reinforcement Learning
International Conference on Machine Learning (ICML), 2021
Roberta Raileanu
Rob Fergus
DRL
OffRL
304
112
0
20 Feb 2021
Training Larger Networks for Deep Reinforcement Learning
Keita Ota
Devesh K. Jha
Asako Kanezaki
OffRL
223
44
0
16 Feb 2021
Rethinking the Implementation Tricks and Monotonicity Constraint in Cooperative Multi-Agent Reinforcement Learning
Jian Hu
Siyang Jiang
Seth Austin Harding
Haibin Wu
Shihua Liao
689
106
0
06 Feb 2021
Differentiable Trust Region Layers for Deep Reinforcement Learning
International Conference on Learning Representations (ICLR), 2021
Fabian Otto
P. Becker
Ngo Anh Vien
Hanna Ziesche
Gerhard Neumann
OffRL
171
22
0
22 Jan 2021
First-Order Problem Solving through Neural MCTS based Reinforcement Learning
Ruiyang Xu
Prashank Kadam
K. Lieberherr
LRM
136
4
0
11 Jan 2021
Faster Policy Learning with Continuous-Time Gradients
Conference on Learning for Dynamics & Control (L4DC), 2020
Samuel K. Ainsworth
Kendall Lowrey
John Thickstun
Zaïd Harchaoui
S. Srinivasa
293
14
0
12 Dec 2020
How to Train PointGoal Navigation Agents on a (Sample and Compute) Budget
Adaptive Agents and Multi-Agent Systems (AAMAS), 2020
Erik Wijmans
Irfan Essa
Dhruv Batra
3DPC
277
10
0
11 Dec 2020
Zero-Shot Terrain Generalization for Visual Locomotion Policies
Alejandro Escontrela
George Yu
P. Xu
Atil Iscen
Jie Tan
181
19
0
11 Nov 2020
Observation Space Matters: Benchmark and Optimization Algorithm
IEEE International Conference on Robotics and Automation (ICRA), 2020
J. Kim
Sehoon Ha
OOD
OffRL
219
12
0
02 Nov 2020
What About Inputing Policy in Value Function: Policy Representation and Policy-extended Value Function Approximator
Hongyao Tang
Zhaopeng Meng
Jianye Hao
Chong Chen
D. Graves
...
Hangyu Mao
Wulong Liu
Yaodong Yang
Wenyuan Tao
Li Wang
OffRL
260
6
0
19 Oct 2020
Learning to Locomote: Understanding How Environment Design Matters for Deep Reinforcement Learning
Motion in Games (MIG), 2020
Daniele Reda
Tianxin Tao
M. van de Panne
AI4CE
209
60
0
09 Oct 2020
A Deeper Look at Discounting Mismatch in Actor-Critic Algorithms
Adaptive Agents and Multi-Agent Systems (AAMAS), 2020
Shangtong Zhang
Romain Laroche
H. V. Seijen
Shimon Whiteson
Rémi Tachet des Combes
464
15
0
02 Oct 2020
Emergent Social Learning via Multi-agent Reinforcement Learning
International Conference on Machine Learning (ICML), 2020
Kamal Ndousse
Douglas Eck
Sergey Levine
Natasha Jaques
274
55
0
01 Oct 2020
Revisiting Design Choices in Proximal Policy Optimization
Chloe Ching-Yun Hsu
Celestine Mendler-Dünner
Moritz Hardt
306
62
0
23 Sep 2020
Phasic Policy Gradient
International Conference on Machine Learning (ICML), 2020
K. Cobbe
Jacob Hilton
Oleg Klimov
John Schulman
OffRL
261
179
0
09 Sep 2020
Benchmarking Multi-Agent Deep Reinforcement Learning Algorithms in Cooperative Tasks
Georgios Papoudakis
Filippos Christianos
Lukas Schafer
Stefano V. Albrecht
OffRL
374
308
0
14 Jun 2020
Jointly Learning Environments and Control Policies with Projected Stochastic Gradient Ascent
Journal of Artificial Intelligence Research (JAIR), 2020
Adrien Bolland
Ioannis Boukas
M. Berger
D. Ernst
444
3
0
02 Jun 2020
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