The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
May. 09, 2023

Filed:

Mar. 10, 2021
Applicant:

Versus Llc, Los Angeles, CA (US);

Inventors:

Matthew Dalton Pierce, Culver City, CA (US);

Jon Alexander Peachey, Las Vegas, NV (US);

Assignee:

Versus LLC, Los Angeles, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 5/04 (2023.01); A63F 13/35 (2014.01); G06N 20/00 (2019.01); A63F 13/46 (2014.01); A63F 13/798 (2014.01);
U.S. Cl.
CPC ...
G06N 5/04 (2013.01); A63F 13/35 (2014.09); A63F 13/46 (2014.09); A63F 13/798 (2014.09); G06N 20/00 (2019.01);
Abstract

An in-content challenge platform generates dynamic content for interactive media applications, for example, online games. The system presents dynamic content in connection with interactive media applications. The in-content challenge platform receives in-content challenge criteria based on actions performed by users in interactive media applications. The in-content challenge platform receives event data indicating actions performed by the user within the online game and identifies an in-content challenge associated with the action. And determines whether any in-content challenge is met by the user based on the actions. If the user meets an in-content challenge, the platform dynamically generates content for sending to the user. The system uses artificial intelligence techniques including symbolic artificial intelligence, unsupervised machine learning techniques, and supervised machine learning techniques for generating dynamic content. The system stores symbolic expressions representing constraints and content items and use an inference engine to determine whether content items satisfy constraints.


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