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Learning to Explore with Meta-Policy Gradient

Learning to Explore with Meta-Policy Gradient

13 March 2018
Tianbing Xu
Qiang Liu
Liang Zhao
Jian Peng
ArXivPDFHTML

Papers citing "Learning to Explore with Meta-Policy Gradient"

18 / 18 papers shown
Title
Proximal Policy Optimization Algorithms
Proximal Policy Optimization Algorithms
John Schulman
Filip Wolski
Prafulla Dhariwal
Alec Radford
Oleg Klimov
OffRL
473
19,006
0
20 Jul 2017
Emergence of Locomotion Behaviours in Rich Environments
Emergence of Locomotion Behaviours in Rich Environments
N. Heess
TB Dhruva
S. Sriram
Jay Lemmon
J. Merel
...
Tom Erez
Ziyun Wang
S. M. Ali Eslami
Martin Riedmiller
David Silver
200
937
0
07 Jul 2017
Parameter Space Noise for Exploration
Parameter Space Noise for Exploration
Matthias Plappert
Rein Houthooft
Prafulla Dhariwal
Szymon Sidor
Richard Y. Chen
Xi Chen
Tamim Asfour
Pieter Abbeel
Marcin Andrychowicz
54
596
0
06 Jun 2017
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Chelsea Finn
Pieter Abbeel
Sergey Levine
OOD
818
11,894
0
09 Mar 2017
Learning to reinforcement learn
Learning to reinforcement learn
Jane X. Wang
Z. Kurth-Nelson
Dhruva Tirumala
Hubert Soyer
Joel Z Leibo
Rémi Munos
Charles Blundell
D. Kumaran
M. Botvinick
OffRL
97
978
0
17 Nov 2016
#Exploration: A Study of Count-Based Exploration for Deep Reinforcement
  Learning
#Exploration: A Study of Count-Based Exploration for Deep Reinforcement Learning
Haoran Tang
Rein Houthooft
Davis Foote
Adam Stooke
Xi Chen
Yan Duan
John Schulman
F. Turck
Pieter Abbeel
OffRL
89
771
0
15 Nov 2016
RL$^2$: Fast Reinforcement Learning via Slow Reinforcement Learning
RL2^22: Fast Reinforcement Learning via Slow Reinforcement Learning
Yan Duan
John Schulman
Xi Chen
Peter L. Bartlett
Ilya Sutskever
Pieter Abbeel
OffRL
86
1,018
0
09 Nov 2016
Layer Normalization
Layer Normalization
Jimmy Lei Ba
J. Kiros
Geoffrey E. Hinton
399
10,481
0
21 Jul 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
167
1,477
0
06 Jun 2016
Deep Exploration via Bootstrapped DQN
Deep Exploration via Bootstrapped DQN
Ian Osband
Charles Blundell
Alexander Pritzel
Benjamin Van Roy
121
1,307
0
15 Feb 2016
Asynchronous Methods for Deep Reinforcement Learning
Asynchronous Methods for Deep Reinforcement Learning
Volodymyr Mnih
Adria Puigdomenech Badia
M. Berk Mirza
Alex Graves
Timothy Lillicrap
Tim Harley
David Silver
Koray Kavukcuoglu
191
8,850
0
04 Feb 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
318
13,234
0
09 Sep 2015
Incentivizing Exploration In Reinforcement Learning With Deep Predictive
  Models
Incentivizing Exploration In Reinforcement Learning With Deep Predictive Models
Bradly C. Stadie
Sergey Levine
Pieter Abbeel
89
505
0
03 Jul 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
308
3,434
0
02 Apr 2015
Trust Region Policy Optimization
Trust Region Policy Optimization
John Schulman
Sergey Levine
Philipp Moritz
Michael I. Jordan
Pieter Abbeel
277
6,764
0
19 Feb 2015
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
1.7K
150,006
0
22 Dec 2014
Generalization and Exploration via Randomized Value Functions
Generalization and Exploration via Randomized Value Functions
Ian Osband
Benjamin Van Roy
Zheng Wen
77
314
0
04 Feb 2014
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
123
12,227
0
19 Dec 2013
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