AUTONOMOUS LEARNING OF ACTIONABLE MODELS FROM UNSTRUTURED DATA
Techniques for autonomously generating a domain model and/or an action model based on unstructured data are provided. In one example, a computer implemented method can comprise extracting, by a system operatively coupled to a processor, a plurality of actions from a non-numerical language. The plura...
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Main Authors | , , , , , |
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Format | Patent |
Language | English |
Published |
02.08.2018
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Subjects | |
Online Access | Get full text |
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Summary: | Techniques for autonomously generating a domain model and/or an action model based on unstructured data are provided. In one example, a computer implemented method can comprise extracting, by a system operatively coupled to a processor, a plurality of actions from a non-numerical language. The plurality of actions can achieve a goal. The computer-implemented method can also comprise generating, by the system, a domain model based on the plurality of actions. Further, the computer-implemented method can comprise generating, by the system, an action model based on the domain model. In various embodiments, the action model can comprise an action transition for accomplishing the goal. |
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Bibliography: | Application Number: US201715840548 |