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. 1606.05312
  4. Cited By
Successor Features for Transfer in Reinforcement Learning
v1v2 (latest)

Successor Features for Transfer in Reinforcement Learning

16 June 2016
André Barreto
Will Dabney
Rémi Munos
Jonathan J. Hunt
Tom Schaul
H. V. Hasselt
David Silver
ArXiv (abs)PDFHTML

Papers citing "Successor Features for Transfer in Reinforcement Learning"

3 / 203 papers shown
Title
Deep Reinforcement Learning with Successor Features for Navigation
  across Similar Environments
Deep Reinforcement Learning with Successor Features for Navigation across Similar Environments
Jingwei Zhang
Jost Tobias Springenberg
Joschka Boedecker
Wolfram Burgard
85
295
0
16 Dec 2016
Reinforcement Learning with Unsupervised Auxiliary Tasks
Reinforcement Learning with Unsupervised Auxiliary Tasks
Max Jaderberg
Volodymyr Mnih
Wojciech M. Czarnecki
Tom Schaul
Joel Z Leibo
David Silver
Koray Kavukcuoglu
SSL
119
1,229
0
16 Nov 2016
Towards Deep Symbolic Reinforcement Learning
Towards Deep Symbolic Reinforcement Learning
M. Garnelo
Kai Arulkumaran
Murray Shanahan
117
226
0
18 Sep 2016
Previous
12345