Abstract
The salience of a narrative event is defined as the ease with which an audience member can recall that past event. This paper describes a series of experiments investigating the use of salience as a predictor of player behavior in interactive narrative scenarios. We utilize Indexter, a plan-based model of narrative for reasoning about salience. Indexter defines a mapping of five event indices identified by cognitive science research onto narrative planning event structures. The indices-protagonist, time, space, causality, and intentionality-correspond to the “who, when, where, how, and why” of a narrative event, and represent dimensions by which events can be linked in short-term memory. We first evaluate Indexter's claim that it can effectively model the salience of past events in a player's mind. Next, we demonstrate that salience can be used to predict players' choices for endings in an interactive story, and finally, we demonstrate that the same technique can be applied to influence players to choose certain endings.
Original language | English |
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Article number | 2905230 |
Pages (from-to) | 74-85 |
Number of pages | 12 |
Journal | IEEE Transactions on Games |
Volume | 12 |
Issue number | 1 |
DOIs | |
State | Published - Mar 2020 |
Bibliographical note
Publisher Copyright:© 2019 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See https://www.ieee.org/publications/rights/index.html for more information.
Funding
Manuscript received January 3, 2018; revised January 8, 2019; accepted February 13, 2019. Date of publication March 15, 2019; date of current version March 17, 2020. This work was supported by the National Science Foundation (NSF) under Award IIS-1464127. (Corresponding author: Rachelyn Farrell.) R. Farrell and S. G. Ware are with the Department of Computer Science, University of New Orleans, New Orleans, LA 70148 USA (e-mail:, rfarrell@ uno.edu; [email protected]).
Funders | Funder number |
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National Science Foundation Arctic Social Science Program | IIS-1464127 |
ASJC Scopus subject areas
- Software
- Artificial Intelligence
- Electrical and Electronic Engineering
- Control and Systems Engineering