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The Benefits of Model-Based Generalization in Reinforcement Learning
v1v2v3 (latest)

The Benefits of Model-Based Generalization in Reinforcement Learning

International Conference on Machine Learning (ICML), 2022
4 November 2022
K. Young
Aditya A. Ramesh
Louis Kirsch
Jürgen Schmidhuber
    OffRL
ArXiv (abs)PDFHTML

Papers citing "The Benefits of Model-Based Generalization in Reinforcement Learning"

10 / 10 papers shown
Title
Pre-trained Visual Representations Generalize Where it Matters in Model-Based Reinforcement Learning
Pre-trained Visual Representations Generalize Where it Matters in Model-Based Reinforcement Learning
Scott Jones
Liyou Zhou
Sebastian W. Pattinson
148
0
0
16 Sep 2025
Efficient Generation of Diverse Cooperative Agents with World Models
Efficient Generation of Diverse Cooperative Agents with World Models
Yi Loo
Akshunn Trivedi
Malika Meghjani
115
0
0
09 Jun 2025
Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes
Zijian Wang
Bin Wang
Mingwen Shao
Hongbo Dou
Boxiang Tao
257
0
0
06 Jan 2025
Learning World Models for Unconstrained Goal Navigation
Learning World Models for Unconstrained Goal NavigationNeural Information Processing Systems (NeurIPS), 2024
Yuanlin Duan
Wensen Mao
He Zhu
223
5
0
03 Nov 2024
Physics-Informed Model and Hybrid Planning for Efficient Dyna-Style
  Reinforcement Learning
Physics-Informed Model and Hybrid Planning for Efficient Dyna-Style Reinforcement Learning
Zakariae El Asri
Olivier Sigaud
Nicolas Thome
191
1
0
02 Jul 2024
Dreaming of Many Worlds: Learning Contextual World Models Aids Zero-Shot
  Generalization
Dreaming of Many Worlds: Learning Contextual World Models Aids Zero-Shot Generalization
Sai Prasanna
Karim Farid
Raghu Rajan
André Biedenkapp
284
14
0
16 Mar 2024
On the Limited Representational Power of Value Functions and its Links
  to Statistical (In)Efficiency
On the Limited Representational Power of Value Functions and its Links to Statistical (In)Efficiency
David Cheikhi
Daniel Russo
OffRL
210
0
0
11 Mar 2024
Closing the Gap between TD Learning and Supervised Learning -- A
  Generalisation Point of View
Closing the Gap between TD Learning and Supervised Learning -- A Generalisation Point of ViewInternational Conference on Learning Representations (ICLR), 2024
Raj Ghugare
Matthieu Geist
Glen Berseth
Benjamin Eysenbach
OffRL
299
26
0
20 Jan 2024
Iterative Option Discovery for Planning, by Planning
Iterative Option Discovery for Planning, by Planning
Kenny Young
Richard S. Sutton
375
2
0
02 Oct 2023
Equivariant Data Augmentation for Generalization in Offline
  Reinforcement Learning
Equivariant Data Augmentation for Generalization in Offline Reinforcement Learning
Cristina Pinneri
Sarah Bechtle
Markus Wulfmeier
Arunkumar Byravan
Jingwei Zhang
William F. Whitney
Martin Riedmiller
OffRL
128
2
0
14 Sep 2023
1