Conditional Sequence Modeling for Safe Reinforcement Learning
Offline safe reinforcement learning (RL) aims to learn policies from a fixed dataset while maximizing performance under cumulative cost constraints. In practice, deployment requirements often vary across scenarios, necessitating a single policy capable of zero-shot adaptation to different cost thres...
Сохранить в:
| Главные авторы: | , , , , , |
|---|---|
| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
MDPI AG
2026-03-01
|
| Серии: | Mathematics |
| Предметы: | |
| Online-ссылка: | https://www.mdpi.com/2227-7390/14/6/1015 |
| Метки: |
Нет меток, Требуется 1-ая метка записи!
|