Handling long and richly constrained tasks through constrained hierarchical reinforcement learning
Safety in goal directed Reinforcement Learning (RL) settings has typically been handled through constraints over trajectories and have demonstrated good performance in primarily short horizon tasks. In this paper, we are specifically interested in the problem of solving temporally extended decision...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | text |
| Language: | English |
| Published: |
Institutional Knowledge at Singapore Management University
2024
|
| Subjects: | |
| Online Access: | https://ink.library.smu.edu.sg/sis_research/8595 https://ink.library.smu.edu.sg/context/sis_research/article/9598/viewcontent/handling_long.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | Singapore Management University |
| Language: | English |