Customized models for imitating player gameplay in a video game
US10940393B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 2, 2019 |
| Grant date | Mar 9, 2021 |
| Priority date | — |
| Expiry date | Jul 2, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N7/01
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems and methods are disclosed for training a machine learning model to control an in-game character or other entity in a video game in a manner that aims to imitate how a particular player would control the character or entity. A generic behavior model that is trained without respect to the particular player may be obtained and then customized based on observed gameplay of the particular player. The customization training process may include freezing at least a subset of layers or levels in the generic model, then generating one or more additional layers or levels that are trained using gameplay data for the particular player.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.