Papers by Je-Wei Jang
AVAST: Attentive Variational State Tracker in a Reinforced Navigator (2022.aacl-main)
Copied to clipboard
| Challenge: | Recent advances in reinforcement learning have been proposed to deal with robotic navigation problems, especially vision-and-language navigation task. |
| Approach: | They propose a method to approximate belief state distribution for the construction of a reinforced navigator by using a variational approach to approximate the unseen environment. |
| Outcome: | The proposed method improves generalization to the unseen environment which is barely achieved by traditional deterministic state tracker. |