Using artificial intelligence to select and chain models for robotic process automation
AssigneeUiPath, Inc.
InventorPrabhdeep Singh
Life of this patent
Estimating the term…
Abstract
Using artificial intelligence (AI) to select and/or chain robotic process automation (RPA) models a given problem is disclosed. A model of models (e.g., an RPA robot or an ML model) may serve as an additional layer on an existing system that makes the existing models more effective. This model of models may incorporate AI that learns an improved or best set of rules or an order from existing models, potentially taking certain activities from a model, feeding input from one model into another, and/or chaining models in some embodiments.
Claims19
A computer-implemented method for using artificial intelligence (AI) to select and/or chain machine learning (ML) models for robotic process automation (RPA), comprising:
- executing, by a computing system, a model of models that analyzes performance of individual ML models and chains of ML models in an ML model pool to be called in a workflow of an RPA robot;
- and
- responsive to a superior performance outcome to an existing ML model or an existing chain of ML models being discovered by the model of models:
- deploying the discovered ML model or the discovered chain of ML models, by the computing system, and replacing the existing ML model or the existing chain of ML models, wherein
- the analysis of the performance of the individual ML models and the chains of ML models comprises performing AI-based experimentation on permutations of chained ML models in series, in parallel, or a combination thereof, and analyzing results output by the individual ML models and the chains of ML models.
A computer-implemented method for using artificial intelligence (AI) to select and/or chain machine learning (ML) models for robotic process automation (RPA), comprising:
- executing, by a computing system, a model of models that analyzes performance of individual ML models and chains of ML models in an ML model pool to be called in a workflow of an RPA robot;
- and
- responsive to a superior performance outcome to an existing ML model or an existing chain of ML models being discovered by the model of models:
- deploying the discovered ML model or the discovered chain of ML models, by the computing system, and replacing the existing ML model or the existing chain of ML models, and
- modifying the workflow of the RPA robot, by the computing system or another computing system, to call the discovered ML model or the discovered chain of ML models, wherein
- the analysis of the performance of the individual ML models and the chains of ML models comprises performing AI-based experimentation on permutations of chained ML models in series, in parallel, or a combination thereof, and analyzing results output by the individual ML models and the chains of ML models.
A computer-implemented method for using artificial intelligence (AI) to select and/or chain machine learning (ML) models for robotic process automation (RPA), comprising:
- executing, by a computing system, a model of models that analyzes performance of individual ML models and chains of ML models in an ML model pool to be called in a workflow of an RPA robot;
- and
- responsive to a superior performance outcome to an existing ML model or an existing chain of ML models being discovered by the model of models:
- deploying the discovered ML model or the discovered chain of ML models, by the computing system, and replacing the existing ML model or the existing chain of ML models, wherein
- the model of models is an ML model or an RPA robot, and
- the analysis of the performance of the individual ML models and the chains of ML models comprises performing AI-based experimentation on permutations of chained ML models in series, in parallel, or a combination thereof, and analyzing results output by the individual ML models and the chains of ML models.
Dependencies are inferred from the claim text.