Inserting probabilistic models in deterministic workflows for robotic process automation and supervisor system
US12306736B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 30, 2023 |
| Grant date | May 20, 2025 |
| Priority date | — |
| Expiry date | Oct 30, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N7/01
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Probabilistic models may be used in a deterministic workflow for robotic process automation (RPA). Machine learning (ML) introduces a probabilistic framework where the outcome is not deterministic, and therefore, the steps are not deterministic. Deterministic workflows may be mixed with probabilistic workflows, or probabilistic activities may be inserted into deterministic workflows, in order to create more dynamic workflows. A supervisor system may be used to monitor an ML model and raise an alarm, disable an RPA robot, bypass an RPA robot, or roll back to a previous version of the ML model when an error is detected by a data drift detector, a concept drift detector, or both.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.