Reinforcement learning using advantage estimates
US11288568B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Feb 9, 2017 |
| Grant date | Mar 29, 2022 |
| Priority date | — |
| Expiry date | Mar 16, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N7/01
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for computing Q values for actions to be performed by an agent interacting with an environment from a continuous action space of actions. In one aspect, a system includes a value subnetwork configured to receive an observation characterizing a current state of the environment and process the observation to generate a value estimate; a policy subnetwork configured to receive the observation and process the observation to generate an ideal point in the continuous action space; and a subsystem configured to receive a particular point in the continuous action space representing a particular action; generate an advantage estimate for the particular action; and generate a Q value for the particular action that is an estimate of an expected return resulting from the agent performing the particular action when the environment is in the current state.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.