ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1612.05533
  4. Cited By
Deep Reinforcement Learning with Successor Features for Navigation
  across Similar Environments
v1v2v3 (latest)

Deep Reinforcement Learning with Successor Features for Navigation across Similar Environments

16 December 2016
Jingwei Zhang
Jost Tobias Springenberg
Joschka Boedecker
Wolfram Burgard
ArXiv (abs)PDFHTML

Papers citing "Deep Reinforcement Learning with Successor Features for Navigation across Similar Environments"

21 / 21 papers shown
Title
SR-Reward: Taking The Path More Traveled
SR-Reward: Taking The Path More Traveled
Seyed Mahdi Basiri Azad
Zahra Padar
Gabriel Kalweit
Joschka Boedecker
OffRL
153
0
0
04 Jan 2025
Non-Adversarial Inverse Reinforcement Learning via Successor Feature Matching
Non-Adversarial Inverse Reinforcement Learning via Successor Feature Matching
A. Jain
Harley Wiltzer
Jesse Farebrother
Irina Rish
Glen Berseth
Sanjiban Choudhury
120
2
0
11 Nov 2024
Efficient Diversity-based Experience Replay for Deep Reinforcement Learning
Efficient Diversity-based Experience Replay for Deep Reinforcement Learning
Kaiyan Zhao
Yiming Wang
Yuyang Chen
Yan Li
Leong Hou U
Xiaoguang Niu
107
1
0
27 Oct 2024
A Survey of Deep Network Solutions for Learning Control in Robotics:
  From Reinforcement to Imitation
A Survey of Deep Network Solutions for Learning Control in Robotics: From Reinforcement to Imitation
L. Tai
Jingwei Zhang
Ming-Yuan Liu
Joschka Boedecker
Wolfram Burgard
OffRL
123
78
0
21 Dec 2016
Towards Cognitive Exploration through Deep Reinforcement Learning for
  Mobile Robots
Towards Cognitive Exploration through Deep Reinforcement Learning for Mobile Robots
L. Tai
Ming-Yuan Liu
58
103
0
06 Oct 2016
Target-driven Visual Navigation in Indoor Scenes using Deep
  Reinforcement Learning
Target-driven Visual Navigation in Indoor Scenes using Deep Reinforcement Learning
Yuke Zhu
Roozbeh Mottaghi
Eric Kolve
Joseph J. Lim
Abhinav Gupta
Li Fei-Fei
Ali Farhadi
VGen
79
1,527
0
16 Sep 2016
Successor Features for Transfer in Reinforcement Learning
Successor Features for Transfer in Reinforcement Learning
André Barreto
Will Dabney
Rémi Munos
Jonathan J. Hunt
Tom Schaul
H. V. Hasselt
David Silver
47
577
0
16 Jun 2016
Progressive Neural Networks
Progressive Neural Networks
Andrei A. Rusu
Neil C. Rabinowitz
Guillaume Desjardins
Hubert Soyer
J. Kirkpatrick
Koray Kavukcuoglu
Razvan Pascanu
R. Hadsell
CLLAI4CE
83
2,465
0
15 Jun 2016
Deep Successor Reinforcement Learning
Deep Successor Reinforcement Learning
Tejas D. Kulkarni
A. Saeedi
Simanta Gautam
S. Gershman
74
209
0
08 Jun 2016
Dueling Network Architectures for Deep Reinforcement Learning
Dueling Network Architectures for Deep Reinforcement Learning
Ziyun Wang
Tom Schaul
Matteo Hessel
H. V. Hasselt
Marc Lanctot
Nando de Freitas
OffRL
91
3,769
0
20 Nov 2015
Actor-Mimic: Deep Multitask and Transfer Reinforcement Learning
Actor-Mimic: Deep Multitask and Transfer Reinforcement Learning
Emilio Parisotto
Jimmy Lei Ba
Ruslan Salakhutdinov
OffRL
113
600
0
19 Nov 2015
Policy Distillation
Policy Distillation
Andrei A. Rusu
Sergio Gomez Colmenarejo
Çağlar Gülçehre
Guillaume Desjardins
J. Kirkpatrick
Razvan Pascanu
Volodymyr Mnih
Koray Kavukcuoglu
R. Hadsell
103
696
0
19 Nov 2015
Prioritized Experience Replay
Prioritized Experience Replay
Tom Schaul
John Quan
Ioannis Antonoglou
David Silver
OffRL
231
3,796
0
18 Nov 2015
Deep Reinforcement Learning with Double Q-learning
Deep Reinforcement Learning with Double Q-learning
H. V. Hasselt
A. Guez
David Silver
OffRL
177
7,665
0
22 Sep 2015
Deep Spatial Autoencoders for Visuomotor Learning
Deep Spatial Autoencoders for Visuomotor Learning
Chelsea Finn
X. Tan
Yan Duan
Trevor Darrell
Sergey Levine
Pieter Abbeel
SSL
62
552
0
21 Sep 2015
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
330
13,289
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
315
3,444
0
02 Apr 2015
Distilling the Knowledge in a Neural Network
Distilling the Knowledge in a Neural Network
Geoffrey E. Hinton
Oriol Vinyals
J. Dean
FedML
367
19,745
0
09 Mar 2015
Trust Region Policy Optimization
Trust Region Policy Optimization
John Schulman
Sergey Levine
Philipp Moritz
Michael I. Jordan
Pieter Abbeel
283
6,801
0
19 Feb 2015
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
2.1K
150,364
0
22 Dec 2014
How transferable are features in deep neural networks?
How transferable are features in deep neural networks?
J. Yosinski
Jeff Clune
Yoshua Bengio
Hod Lipson
OOD
238
8,363
0
06 Nov 2014
1