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INSERTING PROBABILISTIC MODELS IN DETERMINISTIC WORKFLOWS FOR ROBOTIC PROCESS AUTOMATION AND SUPERVISOR SYSTEM
INSERTING PROBABILISTIC MODELS IN DETERMINISTIC WORKFLOWS FOR ROBOTIC PROCESS AUTOMATION AND SUPERVISOR SYSTEM
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机译:用于机器人过程自动化和主管系统的确定性工作流程中插入概率模型
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摘要
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.
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