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Shaping Rewards for Reinforcement Learning with Imperfect Demonstrations
  using Generative Models

Shaping Rewards for Reinforcement Learning with Imperfect Demonstrations using Generative Models

IEEE International Conference on Robotics and Automation (ICRA), 2020
2 November 2020
Yuchen Wu
Melissa Mozifian
Florian Shkurti
ArXiv (abs)PDFHTML

Papers citing "Shaping Rewards for Reinforcement Learning with Imperfect Demonstrations using Generative Models"

14 / 14 papers shown
Dynamic Action Interpolation: A Universal Approach for Accelerating Reinforcement Learning with Expert Guidance
Dynamic Action Interpolation: A Universal Approach for Accelerating Reinforcement Learning with Expert Guidance
Wenjun Cao
264
0
0
26 Apr 2025
Improving the Effectiveness of Potential-Based Reward Shaping in Reinforcement Learning
Improving the Effectiveness of Potential-Based Reward Shaping in Reinforcement LearningAdaptive Agents and Multi-Agent Systems (AAMAS), 2025
Henrik Müller
Daniel Kudenko
OffRL
430
7
0
03 Feb 2025
Highly Efficient Self-Adaptive Reward Shaping for Reinforcement Learning
Highly Efficient Self-Adaptive Reward Shaping for Reinforcement LearningInternational Conference on Learning Representations (ICLR), 2024
Haozhe Ma
Zhengding Luo
Thanh Vinh Vo
Kuankuan Sima
Tze-Yun Leong
829
20
0
06 Aug 2024
Single-Reset Divide & Conquer Imitation Learning
Single-Reset Divide & Conquer Imitation Learning
Alexandre Chenu
Olivier Serris
Olivier Sigaud
Nicolas Perrin-Gilbert
269
0
0
14 Feb 2024
Learning to Navigate from Scratch using World Models and Curiosity: the
  Good, the Bad, and the Ugly
Learning to Navigate from Scratch using World Models and Curiosity: the Good, the Bad, and the Ugly
Daria de Tinguy
Sven Remmery
Pietro Mazzaglia
Tim Verbelen
Bart Dhoedt
370
1
0
30 Aug 2023
Would I have gotten that reward? Long-term credit assignment by
  counterfactual contribution analysis
Would I have gotten that reward? Long-term credit assignment by counterfactual contribution analysisNeural Information Processing Systems (NeurIPS), 2023
Alexander Meulemans
Simon Schug
Seijin Kobayashi
Nathaniel D. Daw
Gregory Wayne
417
7
0
29 Jun 2023
Learning from Guided Play: Improving Exploration for Adversarial
  Imitation Learning with Simple Auxiliary Tasks
Learning from Guided Play: Improving Exploration for Adversarial Imitation Learning with Simple Auxiliary TasksIEEE Robotics and Automation Letters (RA-L), 2022
Trevor Ablett
Bryan Chan
Jonathan Kelly
486
13
0
30 Dec 2022
Few-Shot Preference Learning for Human-in-the-Loop RL
Few-Shot Preference Learning for Human-in-the-Loop RLConference on Robot Learning (CoRL), 2022
Joey Hejna
Dorsa Sadigh
OffRL
408
133
0
06 Dec 2022
Reinforcement learning with Demonstrations from Mismatched Task under
  Sparse Reward
Reinforcement learning with Demonstrations from Mismatched Task under Sparse RewardConference on Robot Learning (CoRL), 2022
Yanjiang Guo
Jingyue Gao
Zheng Wu
Chengming Shi
Jianyu Chen
OffRL
335
7
0
03 Dec 2022
D-Shape: Demonstration-Shaped Reinforcement Learning via Goal
  Conditioning
D-Shape: Demonstration-Shaped Reinforcement Learning via Goal ConditioningAdaptive Agents and Multi-Agent Systems (AAMAS), 2022
Caroline Wang
Garrett A. Warnell
Peter Stone
258
4
0
26 Oct 2022
Bayesian Q-learning With Imperfect Expert Demonstrations
Bayesian Q-learning With Imperfect Expert Demonstrations
Fengdi Che
Xiru Zhu
Doina Precup
David Meger
Gregory Dudek
166
4
0
01 Oct 2022
Accelerating Reinforcement Learning for Autonomous Driving using
  Task-Agnostic and Ego-Centric Motion Skills
Accelerating Reinforcement Learning for Autonomous Driving using Task-Agnostic and Ego-Centric Motion SkillsIEEE/RJS International Conference on Intelligent RObots and Systems (IROS), 2022
Tong Zhou
Letian Wang
Ruobing Chen
Wenshuo Wang
Y. Liu
283
22
0
24 Sep 2022
Tolerance-Guided Policy Learning for Adaptable and Transferrable
  Delicate Industrial Insertion
Tolerance-Guided Policy Learning for Adaptable and Transferrable Delicate Industrial InsertionConference on Robot Learning (CoRL), 2021
Boshen Niu
Chenxi Wang
Changliu Liu
253
5
0
04 Aug 2021
A Minimalist Approach to Offline Reinforcement Learning
A Minimalist Approach to Offline Reinforcement LearningNeural Information Processing Systems (NeurIPS), 2021
Scott Fujimoto
S. Gu
OffRL
610
1,081
0
12 Jun 2021
1
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