Hybrid reinforcement learning for autonomous driving
US11480972B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Nov 13, 2019 |
| Grant date | Oct 25, 2022 |
| Priority date | — |
| Expiry date | Dec 7, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/048
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method includes determining a current state of an environment of an autonomous agent, such as a vehicle. The method also includes determining, via a first neural network, a set of actions based on the current state. The method further includes determining whether further analysis of the set of actions is desired. The method selects an action from the set of actions using a model-based solution based on a reward and a risk of the action when further analysis is desired. The method also includes selecting the action from the set of actions according to a metric when further analysis is not desired. The method controls the autonomous agent to perform the selected action.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.