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Asynchronous Methods for Deep Reinforcement Learning

Asynchronous Methods for Deep Reinforcement Learning

4 February 2016
Volodymyr Mnih
Adria Puigdomenech Badia
M. Berk Mirza
Alex Graves
Timothy Lillicrap
Tim Harley
David Silver
Koray Kavukcuoglu
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Papers citing "Asynchronous Methods for Deep Reinforcement Learning"

12 / 1,612 papers shown
Title
The Option-Critic Architecture
The Option-Critic Architecture
Pierre-Luc Bacon
J. Harb
Doina Precup
OffRL
21
1,071
0
16 Sep 2016
Reward Augmented Maximum Likelihood for Neural Structured Prediction
Reward Augmented Maximum Likelihood for Neural Structured Prediction
Mohammad Norouzi
Samy Bengio
Zhehuai Chen
Navdeep Jaitly
M. Schuster
Yonghui Wu
Dale Schuurmans
35
252
0
01 Sep 2016
Memory-Efficient Backpropagation Through Time
Memory-Efficient Backpropagation Through Time
A. Gruslys
Rémi Munos
Ivo Danihelka
Marc Lanctot
Alex Graves
35
228
0
10 Jun 2016
Safe and Efficient Off-Policy Reinforcement Learning
Safe and Efficient Off-Policy Reinforcement Learning
Rémi Munos
T. Stepleton
Anna Harutyunyan
Marc G. Bellemare
OffRL
86
609
0
08 Jun 2016
Unifying Count-Based Exploration and Intrinsic Motivation
Unifying Count-Based Exploration and Intrinsic Motivation
Marc G. Bellemare
S. Srinivasan
Georg Ostrovski
Tom Schaul
D. Saxton
Rémi Munos
55
1,459
0
06 Jun 2016
OpenAI Gym
OpenAI Gym
Greg Brockman
Vicki Cheung
Ludwig Pettersson
Jonas Schneider
John Schulman
Jie Tang
Wojciech Zaremba
OffRL
ODL
104
5,032
0
05 Jun 2016
Option Discovery in Hierarchical Reinforcement Learning using
  Spatio-Temporal Clustering
Option Discovery in Hierarchical Reinforcement Learning using Spatio-Temporal Clustering
A. Srinivas
Ramnandan Krishnamurthy
Peeyush Kumar
Balaraman Ravindran
27
41
0
17 May 2016
A Deep Hierarchical Approach to Lifelong Learning in Minecraft
A Deep Hierarchical Approach to Lifelong Learning in Minecraft
Chen Tessler
Shahar Givony
Tom Zahavy
D. Mankowitz
Shie Mannor
CLL
36
377
0
25 Apr 2016
Hierarchical Deep Reinforcement Learning: Integrating Temporal
  Abstraction and Intrinsic Motivation
Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation
Tejas D. Kulkarni
Karthik Narasimhan
A. Saeedi
J. Tenenbaum
25
1,127
0
20 Apr 2016
Learning values across many orders of magnitude
Learning values across many orders of magnitude
H. V. Hasselt
A. Guez
Matteo Hessel
Volodymyr Mnih
David Silver
22
169
0
24 Feb 2016
Value Iteration Networks
Value Iteration Networks
Aviv Tamar
Yi Wu
G. Thomas
Sergey Levine
Pieter Abbeel
41
649
0
09 Feb 2016
NetVLAD: CNN architecture for weakly supervised place recognition
NetVLAD: CNN architecture for weakly supervised place recognition
Relja Arandjelović
Petr Gronát
Akihiko Torii
Tomas Pajdla
Josef Sivic
3DV
SSL
88
2,612
0
23 Nov 2015
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