Abstract
Psychological research has demonstrated that as we experience a story several features affect the salience of its events in memory. These features correspond to who? where? when? how? and why? questions about those events. Computational models of salience have been used in interactive narratives to measure which events people most easily remember from the past and which they expect more readily from the future. We use three example domains to show that events in sequences that are solutions to narrative planning problems are generally more salient with each other, and events in non-solution sequences are less salient with each other. This means that measuring the salience of a sequence of actions during planning can serve as an efficient cost function to improve the speed, and perhaps also the quality, of a narrative planner.
| Original language | English |
|---|---|
| Title of host publication | 2022 IEEE Conference on Games, CoG 2022 |
| Pages | 433-440 |
| Number of pages | 8 |
| ISBN (Electronic) | 9781665459891 |
| DOIs | |
| State | Published - 2022 |
| Event | 2022 IEEE Conference on Games, CoG 2022 - Beijing, China Duration: Aug 21 2022 → Aug 24 2022 |
Publication series
| Name | IEEE Conference on Computatonal Intelligence and Games, CIG |
|---|---|
| Volume | 2022-August |
| ISSN (Print) | 2325-4270 |
| ISSN (Electronic) | 2325-4289 |
Conference
| Conference | 2022 IEEE Conference on Games, CoG 2022 |
|---|---|
| Country/Territory | China |
| City | Beijing |
| Period | 8/21/22 → 8/24/22 |
Bibliographical note
Funding Information:This research was supported by the U.S. National Science Foundation, Grant No. IIS-1911053. All opinions are our own.
Publisher Copyright:
© 2022 IEEE.
Keywords
- narrative
- planning
- salience
- search
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Graphics and Computer-Aided Design
- Computer Vision and Pattern Recognition
- Human-Computer Interaction
- Software