Variance Reduced Domain Randomization for Reinforcement Learning With Policy Gradient
By introducing randomness on the environments, domain randomization (DR) imposes diversity to the policy training of deep reinforcement learning, and thus improves its capability of generalization. The randomization of environments, however, introduces another source of variability for the estimate...
Ausführliche Beschreibung
Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 46(2024), 2 vom: 06. Jan., Seite 1031-1048
|
|---|
| 1. Verfasser: |
Jiang, Yuankun
(VerfasserIn) |
|---|
| Weitere Verfasser: |
Li, Chenglin,
Dai, Wenrui,
Zou, Junni,
Xiong, Hongkai |
|---|
| Format: | Online-Aufsatz
|
|---|
| Sprache: | English |
|---|
| Veröffentlicht: |
2024
|
|---|
| Zugriff auf das übergeordnete Werk: | IEEE transactions on pattern analysis and machine intelligence
|
|---|
| Schlagworte: | Journal Article |
|---|