Machine-learned trust scoring for player matchmaking
US11504633B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Feb 1, 2021 |
| Grant date | Nov 22, 2022 |
| Priority date | — |
| Expiry date | Feb 1, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/10
- WIPO fieldFurniture, games
- WIPO sectorOther fields
Abstract
A trained machine learning model(s) is used to determine scores (e.g., trust scores) for user accounts registered with a video game service, and the scores are used to match players together in multiplayer video game settings. In an example process, a computing system may access data associated with registered user accounts, provide the data as input to the trained machine learning model(s), and the trained machine learning model(s) generates the scores as output, which relate to probabilities of players behaving, or not behaving, in accordance with a particular behavior while playing a video game in multiplayer mode. Thereafter, subsets of logged-in user accounts executing a video game can be assigned to different matches based at least in part on the scores determined for those logged-in user accounts, and the video game is executed in the assigned match for each logged-in user account.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.