Reinforcement learning with generalizable gaussian splatting
An excellent representation is crucial for reinforcement learning (RL) performance,
especially in vision-based reinforcement learning tasks. The quality of the environment …
especially in vision-based reinforcement learning tasks. The quality of the environment …
Model-Based Reinforcement Learning with Multi-task Offline Pretraining
Pretraining reinforcement learning (RL) models on offline datasets is a promising way to
improve their training efficiency in online tasks, but challenging due to the inherent mismatch …
improve their training efficiency in online tasks, but challenging due to the inherent mismatch …
Vid2Act: Activate Offline Videos for Visual RL
M Pan, Y Zheng, W Zhang, Y Wang, X Yang - arXiv preprint arXiv …, 2023 - arxiv.org
Pretraining RL models on offline video datasets is a promising way to improve their training
efficiency in online tasks, but challenging due to the inherent mismatch in tasks, dynamics …
efficiency in online tasks, but challenging due to the inherent mismatch in tasks, dynamics …
Information-theoretic state space model for multi-view reinforcement learning
Multi-View Reinforcement Learning (MVRL) seeks to find an optimal control for an agent
given multi-view observations from various sources. Despite recent advances in multi-view …
given multi-view observations from various sources. Despite recent advances in multi-view …
Model-Based Transfer RL with Task-Agnostic Offline Pretraining
M Pan, Y Zheng, H Chen, Y He, Y Wang, X Yang - openreview.net
Pretraining RL models on offline datasets is a promising way to improve their training
efficiency in online tasks, but challenging due to the inherent mismatch in dynamics and …
efficiency in online tasks, but challenging due to the inherent mismatch in dynamics and …