Reward-Consistent Dynamics Models are Strongly Generalizable for Offline Reinforcement Learning

9 October 2023

Papers citing "Reward-Consistent Dynamics Models are Strongly Generalizable for Offline Reinforcement Learning"

8 / 8 papers shown

Title
NeoRL-2: Near Real-World Benchmarks for Offline Reinforcement Learning with Extended Realistic Scenarios Songyi Gao Zuolin Tu Rong-Jun Qin Yi-Hao Sun Xiong-Hui Chen Yang Yu OffRL 31 0 0 25 Mar 2025
Grounded Answers for Multi-agent Decision-making Problem through Generative World Model Zeyang Liu Xinrui Yang Shiguang Sun Long Qian Lipeng Wan Xingyu Chen Xuguang Lan 22 2 0 03 Oct 2024
Offline Model-Based Reinforcement Learning with Anti-Exploration Padmanaba Srinivasan William J. Knottenbelt OffRL 41 0 0 20 Aug 2024
Policy Optimization in RLHF: The Impact of Out-of-preference Data Ziniu Li Tian Xu Yang Yu 15 28 0 17 Dec 2023
Uncertainty-Based Offline Reinforcement Learning with Diversified Q-Ensemble Gaon An Seungyong Moon Jang-Hyun Kim Hyun Oh Song OffRL 92 261 0 04 Oct 2021
COMBO: Conservative Offline Model-Based Policy Optimization Tianhe Yu Aviral Kumar Rafael Rafailov Aravind Rajeswaran Sergey Levine Chelsea Finn OffRL 194 412 0 16 Feb 2021
NeoRL: A Near Real-World Benchmark for Offline Reinforcement Learning Rongjun Qin Songyi Gao Xingyuan Zhang Zhen Xu Shengkai Huang Zewen Li Weinan Zhang Yang Yu OffRL 132 76 0 01 Feb 2021
Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems Sergey Levine Aviral Kumar George Tucker Justin Fu OffRL GP 321 1,662 0 04 May 2020