Improved automatic discovery of subgoals for options in hierarchical
Options have been shown to be a key step in extending reinforcement learning beyond low-level reactionary systems to higher-level, planning systems. Most of the options research involves hand-crafted options; there has been only very limited work in the automated discovery of options. We extend earl...
Guardado en:
| Autores principales: | , , |
|---|---|
| Formato: | Articulo |
| Lenguaje: | Inglés |
| Publicado: |
2003
|
| Materias: | |
| Acceso en línea: | http://sedici.unlp.edu.ar/handle/10915/9461 http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Oct03-2.pdf |
| Aporte de: |
| Sumario: | Options have been shown to be a key step in extending reinforcement learning beyond low-level reactionary systems to higher-level, planning systems. Most of the options research involves hand-crafted options; there has been only very limited work in the automated discovery of options. We extend early work in automated option discovery with a flexible and robust method. |
|---|