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...

Full description

Saved in:
Bibliographic Details
Main Authors Manikonda, Lydia, Srivastava, Biplav, Sohrabi Araghi, Shirin, Turaga, Deepak Srinivas, Riabov, Anton Viktorovich, Talamadupula, Kartik
Format Patent
LanguageEnglish
Published 02.08.2018
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
ELECTRIC DIGITAL DATA PROCESSING
PHYSICS
Online AccessGet full text

Cover

More Information
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.
Bibliography:Application Number: US201715840548