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. 2310.17139
  4. Cited By
Understanding and Addressing the Pitfalls of Bisimulation-based
  Representations in Offline Reinforcement Learning

Understanding and Addressing the Pitfalls of Bisimulation-based Representations in Offline Reinforcement Learning

26 October 2023
Hongyu Zang
Xin-hui Li
Leiji Zhang
Yang Liu
Baigui Sun
Riashat Islam
Rémi Tachet des Combes
Romain Laroche
    OffRL
ArXivPDFHTML

Papers citing "Understanding and Addressing the Pitfalls of Bisimulation-based Representations in Offline Reinforcement Learning"

5 / 5 papers shown
Title
Intrinsic Dynamics-Driven Generalizable Scene Representations for
  Vision-Oriented Decision-Making Applications
Intrinsic Dynamics-Driven Generalizable Scene Representations for Vision-Oriented Decision-Making Applications
Dayang Liang
Jinyang Lai
Yunlong Liu
33
0
0
30 May 2024
An Empirical Investigation of Representation Learning for Imitation
An Empirical Investigation of Representation Learning for Imitation
Xin Chen
Sam Toyer
Cody Wild
Scott Emmons
Ian S. Fischer
...
Steven H. Wang
Ping Luo
Stuart J. Russell
Pieter Abbeel
Rohin Shah
AI4TS
33
27
0
16 May 2022
Offline Reinforcement Learning with Implicit Q-Learning
Offline Reinforcement Learning with Implicit Q-Learning
Ilya Kostrikov
Ashvin Nair
Sergey Levine
OffRL
214
843
0
12 Oct 2021
Decoupling Representation Learning from Reinforcement Learning
Decoupling Representation Learning from Reinforcement Learning
Adam Stooke
Kimin Lee
Pieter Abbeel
Michael Laskin
SSL
DRL
284
341
0
14 Sep 2020
Offline Reinforcement Learning: Tutorial, Review, and Perspectives on
  Open Problems
Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems
Sergey Levine
Aviral Kumar
George Tucker
Justin Fu
OffRL
GP
340
1,960
0
04 May 2020
1