Rpa process adaptive optimization method, system, apparatus, and medium

Abstract

The application discloses an RPA process self-adaptive optimization method, system, device and medium, relates to the technical field of robot process automation, and comprises the following steps: acquiring multi-dimensional environment data in a process execution process, and generating a state feature sequence based on the multi-dimensional environment data; performing abnormality prediction based on the state feature sequence to obtain an abnormality probability prediction value; when the abnormality probability prediction value is greater than a preset probability threshold value, acquiring multi-modal features of a current target user interface, and fusing the multi-modal features into comprehensive scene features; matching the comprehensive scene features with historical strategy features in a knowledge base to determine a target replacement strategy; when a system response corresponding to the target replacement strategy is in a delay state, determining retry waiting parameters corresponding to the target replacement strategy; and updating an execution path in the knowledge base according to an execution result of the target replacement strategy; and the application plays a role of process self-adaptive repair and dynamic optimization of an execution path.

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