Patent · US Active

Evaluating software license usage using reinforcement learning agents

US11854102B2 · kind B2 · utility

0Cited by
3References
20Claims
0Family size

Assignee

Inventors

Key dates

Filing dateMay 2, 2019
Grant dateDec 26, 2023
Priority date
Expiry dateSep 16, 2039

Classification

  • Technology area (CPC G)Physics
  • CPC primaryG06F2201/865
  • WIPO fieldComputer technology
  • WIPO sectorElectrical engineering

Abstract

Techniques are provided for reinforcement learning-based evaluation of software product usage. One method comprises obtaining key performance indicators indicating software product usage by a user; determining, for a predefined time window: (i) a mean and/or a median of the obtained KPIs; (ii) an amount of time that the software product was active; and (iii) an amount of interactions by the user with a user interface; evaluating possible login states of the software product using at least one reinforcement learning agent, wherein the evaluating comprises (a) observing the plurality of possible login states, including a current state comprising a current login state of the software product, and (b) obtaining an expected utility score for changing from the current login state to a different login state of the software product; and determining whether to change from the current login state to a different login state of the software product based on the expected utility score.

Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.