Guiding search in continuous state-action spaces by learning an action sampler from off-target search experience
Copyright © 2018, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved. In robotics, it is essential to be able to plan efficiently in high-dimensional continuous state-action spaces for long horizons. For such complex planning problems, unguided uniform sam...
| Main Authors: | , , |
|---|---|
| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
2021
|
| Online Access: | https://hdl.handle.net/1721.1/137707 |