Got Any Plans? How AI Represents Plans Using Hierarchical Task Networks

Got Any Plans? How AI Represents Plans Using Hierarchical Task Networks

Date

2-14-2024

Faculty Mentor

Monica Trifas, Mathematics, Computing & Information Sciences; Arup Ghosh, Mathematics, Computing & Information Sciences

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Submission Type

Conference Proceeding

Location

1:15-1:25pm | Houston Cole Library, 11th Floor

Description

For an artificial intelligence to be able to solve real-world problems, it must be able to represent knowledge about not only the domain in which it is working, but also knowledge about its own approaches that it derives. When these approaches are complex enough to necessitate planning before any action is taken, the AI has to decompose the space of possible solutions into granular tasks and reassemble them into a structure forming the correct path. One method of accomplishing this is through implementing hierarchical task networks, where the network resembles a tree structure with the addition of preconditions allowing non-linear solution paths to be formed as necessary. This presentation will explain the benefits of this form of knowledge representation for planning and describe some of its successful applications in online safety.

Keywords

student research, computing

Rights

This content is the property of Jacksonville State University and is intended for non-commercial use. Video and images may be copied for personal use, research, teaching or any "fair use" as defined by copyright law. Users are asked to acknowledge Jacksonville State University. For more information, please contact digitalcommons@jsu.edu.

Disciplines

Computer Sciences

Got Any Plans? How AI Represents Plans Using Hierarchical Task Networks

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