Selecting reinforcement learning actions using goals and observations
US10628733B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Apr 6, 2016 |
| Grant date | Apr 21, 2020 |
| Priority date | — |
| Expiry date | May 15, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for reinforcement learning using goals and observations. One of the methods includes receiving an observation characterizing a current state of the environment; receiving a goal characterizing a target state from a set of target states of the environment; processing the observation using an observation neural network to generate a numeric representation of the observation; processing the goal using a goal neural network to generate a numeric representation of the goal; combining the numeric representation of the observation and the numeric representation of the goal to generate a combined representation; processing the combined representation using an action score neural network to generate a respective score for each action in the predetermined set of actions; and selecting the action to be performed using the respective scores for the actions in the predetermined set of actions.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.