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Accelerated Methods for Deep Reinforcement Learning

Accelerated Methods for Deep Reinforcement Learning

7 March 2018
Adam Stooke
Pieter Abbeel
    OffRL
    OnRL
ArXivPDFHTML

Papers citing "Accelerated Methods for Deep Reinforcement Learning"

50 / 65 papers shown
Title
Acceleration for Deep Reinforcement Learning using Parallel and
  Distributed Computing: A Survey
Acceleration for Deep Reinforcement Learning using Parallel and Distributed Computing: A Survey
Zhihong Liu
Xin Xu
Peng Qiao
Dongsheng Li
OffRL
22
2
0
08 Nov 2024
Speeding up Policy Simulation in Supply Chain RL
Speeding up Policy Simulation in Supply Chain RL
Vivek Farias
Joren Gijsbrechts
Aryan I. Khojandi
Tianyi Peng
A. Zheng
38
0
0
04 Jun 2024
SwiftRL: Towards Efficient Reinforcement Learning on Real
  Processing-In-Memory Systems
SwiftRL: Towards Efficient Reinforcement Learning on Real Processing-In-Memory Systems
Kailash Gogineni
Sai Santosh Dayapule
Juan Gómez Luna
Karthikeya Gogineni
Peng Wei
Tian-Shing Lan
Mohammad Sadrosadati
Onur Mutlu
Guru Venkataramani
50
10
0
07 May 2024
XLand-MiniGrid: Scalable Meta-Reinforcement Learning Environments in JAX
XLand-MiniGrid: Scalable Meta-Reinforcement Learning Environments in JAX
Alexander Nikulin
Vladislav Kurenkov
Ilya Zisman
Artem Agarkov
Viacheslav Sinii
Sergey Kolesnikov
26
25
0
19 Dec 2023
Spreeze: High-Throughput Parallel Reinforcement Learning Framework
Spreeze: High-Throughput Parallel Reinforcement Learning Framework
Jing Hou
Guang Chen
Ruiqi Zhang
Zhijun Li
Shangding Gu
Changjun Jiang
OffRL
26
2
0
11 Dec 2023
minimax: Efficient Baselines for Autocurricula in JAX
minimax: Efficient Baselines for Autocurricula in JAX
Minqi Jiang
Michael Dennis
Edward Grefenstette
Tim Rocktaschel
24
8
0
21 Nov 2023
Small batch deep reinforcement learning
Small batch deep reinforcement learning
J. Obando-Ceron
Marc G. Bellemare
Pablo Samuel Castro
VLM
34
14
0
05 Oct 2023
Cleanba: A Reproducible and Efficient Distributed Reinforcement Learning
  Platform
Cleanba: A Reproducible and Efficient Distributed Reinforcement Learning Platform
Shengyi Huang
Jiayi Weng
Rujikorn Charakorn
Min-Bin Lin
Zhongwen Xu
Santiago Ontañón
22
3
0
29 Sep 2023
SRL: Scaling Distributed Reinforcement Learning to Over Ten Thousand
  Cores
SRL: Scaling Distributed Reinforcement Learning to Over Ten Thousand Cores
Zhiyu Mei
Wei Fu
Jiaxuan Gao
Guang Wang
Huanchen Zhang
Yi Wu
OffRL
LRM
29
5
0
29 Jun 2023
Galactic: Scaling End-to-End Reinforcement Learning for Rearrangement at
  100k Steps-Per-Second
Galactic: Scaling End-to-End Reinforcement Learning for Rearrangement at 100k Steps-Per-Second
Vincent-Pierre Berges
Andrew Szot
Devendra Singh Chaplot
Aaron Gokaslan
Roozbeh Mottaghi
Dhruv Batra
Eric Undersander
LRM
LM&Ro
32
5
0
13 Jun 2023
Investigating Navigation Strategies in the Morris Water Maze through
  Deep Reinforcement Learning
Investigating Navigation Strategies in the Morris Water Maze through Deep Reinforcement Learning
A. Liu
Alla Borisyuk
16
6
0
01 Jun 2023
AccMER: Accelerating Multi-Agent Experience Replay with Cache
  Locality-aware Prioritization
AccMER: Accelerating Multi-Agent Experience Replay with Cache Locality-aware Prioritization
Kailash Gogineni
Yongsheng Mei
Peng Wei
Tian-Shing Lan
Guru Venkataramani
18
13
0
31 May 2023
Towards Efficient Multi-Agent Learning Systems
Towards Efficient Multi-Agent Learning Systems
Kailash Gogineni
Peng Wei
Tian-Shing Lan
Guru Venkataramani
27
4
0
22 May 2023
CFlowNets: Continuous Control with Generative Flow Networks
CFlowNets: Continuous Control with Generative Flow Networks
Yinchuan Li
Shuang Luo
Haozhi Wang
Jianye Hao
91
20
0
04 Mar 2023
Distributed Deep Reinforcement Learning: A Survey and A Multi-Player
  Multi-Agent Learning Toolbox
Distributed Deep Reinforcement Learning: A Survey and A Multi-Player Multi-Agent Learning Toolbox
Qiyue Yin
Tongtong Yu
S. Shen
Jun Yang
Meijing Zhao
Kaiqi Huang
Bin Liang
Liangsheng Wang
OffRL
20
13
0
01 Dec 2022
Actively Learning Costly Reward Functions for Reinforcement Learning
Actively Learning Costly Reward Functions for Reinforcement Learning
André Eberhard
Houssam Metni
G. Fahland
A. Stroh
Pascal Friederich
OffRL
35
0
0
23 Nov 2022
Q-Ensemble for Offline RL: Don't Scale the Ensemble, Scale the Batch
  Size
Q-Ensemble for Offline RL: Don't Scale the Ensemble, Scale the Batch Size
Alexander Nikulin
Vladislav Kurenkov
Denis Tarasov
Dmitry Akimov
Sergey Kolesnikov
OffRL
31
14
0
20 Nov 2022
Local Connection Reinforcement Learning Method for Efficient Control of
  Robotic Peg-in-Hole Assembly
Local Connection Reinforcement Learning Method for Efficient Control of Robotic Peg-in-Hole Assembly
Yuhang Gai
Jiwen Zhang
Dan Wu
Ken Chen
OffRL
32
1
0
24 Oct 2022
Scaling up Stochastic Gradient Descent for Non-convex Optimisation
Scaling up Stochastic Gradient Descent for Non-convex Optimisation
S. Mohamad
H. Alamri
A. Bouchachia
47
3
0
06 Oct 2022
MAN: Multi-Action Networks Learning
MAN: Multi-Action Networks Learning
Keqin Wang
Alison Bartsch
A. Farimani
18
3
0
19 Sep 2022
Fast Population-Based Reinforcement Learning on a Single Machine
Fast Population-Based Reinforcement Learning on a Single Machine
Arthur Flajolet
Claire Bizon Monroc
Karim Beguir
Thomas Pierrot
OffRL
24
10
0
17 Jun 2022
Achieving Goals using Reward Shaping and Curriculum Learning
Achieving Goals using Reward Shaping and Curriculum Learning
M. Anca
Jonathan D. Thomas
Dabal Pedamonti
M. Studley
Mark Hansen
4
1
0
06 Jun 2022
Fast and Data Efficient Reinforcement Learning from Pixels via
  Non-Parametric Value Approximation
Fast and Data Efficient Reinforcement Learning from Pixels via Non-Parametric Value Approximation
Alex Long
Alan Blair
H. V. Hoof
23
3
0
07 Mar 2022
GPU-Accelerated Policy Optimization via Batch Automatic Differentiation
  of Gaussian Processes for Real-World Control
GPU-Accelerated Policy Optimization via Batch Automatic Differentiation of Gaussian Processes for Real-World Control
Abdolreza Taheri
Joni Pajarinen
R. Ghabcheloo
GP
19
3
0
28 Feb 2022
Graph augmented Deep Reinforcement Learning in the GameRLand3D
  environment
Graph augmented Deep Reinforcement Learning in the GameRLand3D environment
E. Beeching
Maxim Peter
Philippe Marcotte
Jilles Debangoye
Olivier Simonin
Joshua Romoff
Christian Wolf
11
5
0
22 Dec 2021
Godot Reinforcement Learning Agents
Godot Reinforcement Learning Agents
E. Beeching
Jilles Debangoye
Olivier Simonin
Christian Wolf
GP
OnRL
18
5
0
07 Dec 2021
Fast and Data-Efficient Training of Rainbow: an Experimental Study on
  Atari
Fast and Data-Efficient Training of Rainbow: an Experimental Study on Atari
Dominik Schmidt
Thomas Schmied
OffRL
20
12
0
19 Nov 2021
Human-Level Control without Server-Grade Hardware
Human-Level Control without Server-Grade Hardware
Brett Daley
Chris Amato
BDL
OffRL
8
0
0
01 Nov 2021
Improving Robustness of Reinforcement Learning for Power System Control
  with Adversarial Training
Improving Robustness of Reinforcement Learning for Power System Control with Adversarial Training
Alexander Pan
Yongkyun Lee
Huan Zhang
Yize Chen
Yuanyuan Shi
AAML
20
17
0
18 Oct 2021
Learning to Walk in Minutes Using Massively Parallel Deep Reinforcement
  Learning
Learning to Walk in Minutes Using Massively Parallel Deep Reinforcement Learning
Nikita Rudin
David Hoeller
Philipp Reist
Marco Hutter
115
545
0
24 Sep 2021
Tianshou: a Highly Modularized Deep Reinforcement Learning Library
Tianshou: a Highly Modularized Deep Reinforcement Learning Library
Jiayi Weng
Huayu Chen
Dong Yan
Kaichao You
Alexis Duburcq
Minghao Zhang
Yi Su
Hang Su
Jun Zhu
NoLa
OffRL
18
194
0
29 Jul 2021
Deep Learning for Embodied Vision Navigation: A Survey
Deep Learning for Embodied Vision Navigation: A Survey
Fengda Zhu
Yi Zhu
Vincent CS Lee
Xiaodan Liang
Xiaojun Chang
EgoV
LM&Ro
42
0
0
07 Jul 2021
MALib: A Parallel Framework for Population-based Multi-agent
  Reinforcement Learning
MALib: A Parallel Framework for Population-based Multi-agent Reinforcement Learning
Ming Zhou
Bo Liu
Hanjing Wang
Muning Wen
Runzhe Wu
Ying Wen
Yaodong Yang
Weinan Zhang
Jun Wang
OffRL
22
46
0
05 Jun 2021
Podracer architectures for scalable Reinforcement Learning
Podracer architectures for scalable Reinforcement Learning
Matteo Hessel
M. Kroiss
Aidan Clark
Iurii Kemaev
John Quan
Thomas Keck
Fabio Viola
H. V. Hasselt
16
37
0
13 Apr 2021
Scaling Scaling Laws with Board Games
Scaling Scaling Laws with Board Games
Andrew Jones
8
39
0
07 Apr 2021
Progressive extension of reinforcement learning action dimension for
  asymmetric assembly tasks
Progressive extension of reinforcement learning action dimension for asymmetric assembly tasks
Yuhang Gai
Jiuming Guo
Dan Wu
Ken Chen
11
0
0
06 Apr 2021
Training Larger Networks for Deep Reinforcement Learning
Training Larger Networks for Deep Reinforcement Learning
Keita Ota
Devesh K. Jha
Asako Kanezaki
OffRL
23
39
0
16 Feb 2021
Rethinking the Implementation Tricks and Monotonicity Constraint in
  Cooperative Multi-Agent Reinforcement Learning
Rethinking the Implementation Tricks and Monotonicity Constraint in Cooperative Multi-Agent Reinforcement Learning
Jian Hu
Siyang Jiang
Seth Austin Harding
Haibin Wu
Shihua Liao
16
86
0
06 Feb 2021
Towards Understanding Asynchronous Advantage Actor-critic: Convergence
  and Linear Speedup
Towards Understanding Asynchronous Advantage Actor-critic: Convergence and Linear Speedup
Han Shen
Kaipeng Zhang
Min-Fong Hong
Tianyi Chen
32
28
0
31 Dec 2020
The Architectural Implications of Distributed Reinforcement Learning on
  CPU-GPU Systems
The Architectural Implications of Distributed Reinforcement Learning on CPU-GPU Systems
A. Inci
Evgeny Bolotin
Yaosheng Fu
Gal Dalal
Shie Mannor
D. Nellans
Diana Marculescu
AI4CE
17
13
0
08 Dec 2020
Applied Machine Learning for Games: A Graduate School Course
Applied Machine Learning for Games: A Graduate School Course
Yilei Zeng
Aayush Shah
Jameson Thai
M. Zyda
AI4CE
9
3
0
30 Nov 2020
Integrating Distributed Architectures in Highly Modular RL Libraries
Integrating Distributed Architectures in Highly Modular RL Libraries
Albert Bou
Sebastian Dittert
Gianni De Fabritiis
23
0
0
06 Jul 2020
Review, Analysis and Design of a Comprehensive Deep Reinforcement
  Learning Framework
Review, Analysis and Design of a Comprehensive Deep Reinforcement Learning Framework
Ngoc Duy Nguyen
Thanh Thi Nguyen
Hai V. Nguyen
Doug Creighton
S. Nahavandi
32
3
0
27 Feb 2020
Non-asymptotic Convergence of Adam-type Reinforcement Learning
  Algorithms under Markovian Sampling
Non-asymptotic Convergence of Adam-type Reinforcement Learning Algorithms under Markovian Sampling
Huaqing Xiong
Tengyu Xu
Yingbin Liang
Wei Zhang
17
33
0
15 Feb 2020
DD-PPO: Learning Near-Perfect PointGoal Navigators from 2.5 Billion
  Frames
DD-PPO: Learning Near-Perfect PointGoal Navigators from 2.5 Billion Frames
Erik Wijmans
Abhishek Kadian
Ari S. Morcos
Stefan Lee
Irfan Essa
Devi Parikh
Manolis Savva
Dhruv Batra
26
467
0
01 Nov 2019
Asynchronous Methods for Model-Based Reinforcement Learning
Asynchronous Methods for Model-Based Reinforcement Learning
Yunzhi Zhang
I. Clavera
Bo-Yu Tsai
Pieter Abbeel
OffRL
11
27
0
28 Oct 2019
LIMIS: Locally Interpretable Modeling using Instance-wise Subsampling
LIMIS: Locally Interpretable Modeling using Instance-wise Subsampling
Jinsung Yoon
Sercan Ö. Arik
Tomas Pfister
FAtt
8
2
0
26 Sep 2019
rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch
rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch
Adam Stooke
Pieter Abbeel
OffRL
19
96
0
03 Sep 2019
Reusability and Transferability of Macro Actions for Reinforcement
  Learning
Reusability and Transferability of Macro Actions for Reinforcement Learning
Yi-Hsiang Chang
Kuan-Yu Chang
Henry Kuo
Chun-Yi Lee
13
2
0
05 Aug 2019
Accelerating Reinforcement Learning through GPU Atari Emulation
Accelerating Reinforcement Learning through GPU Atari Emulation
Steven Dalton
I. Frosio
M. Garland
ELM
19
9
0
19 Jul 2019
12
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