Method and apparatus for task scheduling based on deep reinforcement learning, and device
US11886993B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 9, 2020 |
| Grant date | Jan 30, 2024 |
| Priority date | — |
| Expiry date | Oct 1, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG08G1/0125
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Disclosed are a method and apparatus for task scheduling based on deep reinforcement learning and a device. The method comprises: obtaining multiple target subtasks to be scheduled; building target state data corresponding to the multiple target subtasks, wherein the target state data comprises a first set, a second set, a third set, and a fourth set; inputting the target state data into a pre-trained task scheduling model, to obtain a scheduling result of each target subtask; wherein, the scheduling result of each target subtask comprises a probability that the target subtask is scheduled to each target node; for each target subtask, determining a target node to which the target subtask is to be scheduled based on the scheduling result of the target subtask, and scheduling the target subtask to the determined target node.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.