Methods and systems for support policy learning
US11605026B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | May 15, 2020 |
| Grant date | Mar 14, 2023 |
| Priority date | — |
| Expiry date | May 27, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/084
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Methods and systems are described for support policy learning in an agent of a robot. A general value function (GVF) is learned for a main policy, where the GVF represents future performance of the agent executing the main policy for a given state of the environment. A master policy selects an action based on the predicted accumulated success value received from the general value function. When the predicted accumulated success value is an acceptable value, the action selected by the master policy is execution of the main policy. When the predicted accumulated success value is not an acceptable value, the master action causes a support policy to be learned. The support policy generates a support action to be performed which causes the robot to transition from to a new state where the predicted accumulated success value has an acceptable value.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.