Reinforcement learning agent training method, modal bandwidth resource scheduling method and apparatus
US11979295B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 26, 2023 |
| Grant date | May 7, 2024 |
| Priority date | — |
| Expiry date | Jul 26, 2043 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04L41/40
- WIPO fieldDigital communication
- WIPO sectorElectrical engineering
Abstract
The present disclosure discloses a reinforcement learning agent training method, modal bandwidth resource scheduling method and apparatus. The reinforcement learning agent training method utilizes a reinforcement learning agent to continuously interact with a network environment in a polymorphic smart network to obtain the latest global network characteristics and output updated actions. By adjusting the bandwidth occupied by modals, a reward value is set to determine an optimization target for the agent, the scheduling of modals is realized, and the rational use of polymorphic smart network resources is guaranteed. The trained reinforcement learning agent is applied to the modal bandwidth resource scheduling method, and can adapt to networks with different characteristics, and thus can be used for intelligent management and control of polymorphic smart networks and has good adaptability and scheduling performance.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.