Reinforcement learning using pseudo-counts
US11727264B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | May 18, 2017 |
| Grant date | Aug 15, 2023 |
| Priority date | — |
| Expiry date | Sep 5, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/092
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a neural network used to select actions to be performed by an agent interacting with an environment. One of the methods includes obtaining data identifying (i) a first observation characterizing a first state of the environment, (ii) an action performed by the agent in response to the first observation, and (iii) an actual reward received resulting from the agent performing the action in response to the first observation; determining a pseudo-count for the first observation; determining an exploration reward bonus that incentivizes the agent to explore the environment from the pseudo-count for the first observation; generating a combined reward from the actual reward and the exploration reward bonus; and adjusting current values of the parameters of the neural network using the combined reward.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.