Of intent and action : implementing personality traits for storytelling through concept patterns
Name
872117234-MIT.pdf
Description
Full printable version
Size
8.58 MB
Format
Adobe PDF
Checksum (MD5)
081f93a36836ec20277f463e7d0f56a1
Author(s)
Song, Susan S. (Susan Shuchen)
Advisor(s)
Patrick H. Winston.
Alternative Title
Implementing personality traits for storytelling through concept patterns
Date Issued
2012
Publisher
Massachusetts Institute of Technology
Abstract
Personality traits such as "kind," "aggressive," and "brave" are integral to storytelling because they impart succinct descriptors of character personalities. Authors apply traits to characters, readers infer characters' traits from the narrative, and readers learn the meaning of new traits. For instance, a reader can learn the personality trait "vindictive" from Alexandre Dumas's novel The Count of Monte Cristo and then use this trait to predict or explain a character's behavior. The reader can also infer that a character from this novel, such as Edmond Dantes, is "vindictive" without needing Dumas to explicitly describe the character with this trait. With the goal of enabling computational storytelling systems to perform the abilities stated above, I present in this thesis a concept pattern-based approach to representing intentional personality traits. I articulate the processes of trait learning, application, and inference and provide steps and insights to how these processes can be computationally implemented. I also give examples of ten personality traits represented using concept patterns inside the Genesis system and show how these traits are discovered inside well-known historical narratives and works of fiction.
Description
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2012.
Cataloged from PDF version of thesis.
Includes bibliographical references (page 97).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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