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Conference

International Conference on Interactive Digital Storytelling 

About: International Conference on Interactive Digital Storytelling is an academic conference. The conference publishes majorly in the area(s): Narrative & Interactive storytelling. Over the lifetime, 588 publication(s) have been published by the conference receiving 4034 citation(s).
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Book ChapterDOI
21 Nov 2009
TL;DR: An approach to planning with trajectory constraints is developed that decomposes the problem into a set of smaller subproblems using the temporal orderings described by the constraints and then solves them incrementally.
Abstract: AI planning has featured in a number of Interactive Storytelling prototypes: since narratives can be naturally modelled as a sequence of actions it is possible to exploit state of the art planners in the task of narrative generation. However the characteristics of a "good" plan, such as optimality, aren't necessarily the same as those of a "good" narrative, where errors and convoluted sequences may offer more reader interest, so some narrative structuring is required. We have looked at injecting narrative control into plan generation through the use of PDDL3.0 state trajectory constraints which enable us to express narrative control information within the planning representation. As part of this we have developed an approach to planning with trajectory constraints. The approach decomposes the problem into a set of smaller subproblems using the temporal orderings described by the constraints and then solves them incrementally. In this paper we outline our method and present results that illustrate the potential of the approach.

91 citations


Book ChapterDOI
26 Nov 2008
TL;DR: A computational method for generating flashback and foreshadowing, specifically targeted at the evocation of surprise in the reader's mind, focuses on surprise as a cognitive response rather than as an emotional response.
Abstract: This paper describes work currently in progress to develop a computational method for generating flashback and foreshadowing, specifically targeted at the evocation of surprise in the reader's mind. Flashback provides a backstory to explain what caused the surprise outcome. Foreshadowing provides an implicit hint about the surprise. Our study focuses on surprise as a cognitive response rather than as an emotional response. The reader's story construction process is simulated by a plan-based reader model that checks unexpectedness and postdictability of the surprise.

83 citations


Book ChapterDOI
26 Nov 2008
TL;DR: This paper presents a system where the user and computer take turns in writing sentences of a fictional narrative, selected from a collection of millions of stories extracted from Internet weblogs.
Abstract: Interactive storytelling is an interesting cross-disciplinary area that has importance in research as well as entertainment In this paper we explore a new area of interactive storytelling that blurs the line between traditional interactive fiction and collaborative writing We present a system where the user and computer take turns in writing sentences of a fictional narrative Sentences contributed by the computer are selected from a collection of millions of stories extracted from Internet weblogs By leveraging the large amounts of personal narrative content available on the web, we show that even with a simple approach our system can produce compelling stories with our users

71 citations


Book ChapterDOI
26 Nov 2008
TL;DR: A system that produces a narrative designed specifically to evoke suspense from the reader is developed and an empirical evaluation provides strong support for the claim that the system is effective in generating suspenseful stories.
Abstract: Although suspense contributes significantly to the enjoyment of a narrative by its readers, there has been little research on the automated generation of stories that evoke specific cognitive and affective responses in their readers. The goal of this research is to develop and evaluate a system that produces a narrative designed specifically to evoke suspense from the reader. The system takes as input a plan data structure representing the goals of a storyworld's characters and the actions they perform in pursuit of them. Adapting theories developed by cognitive psychologists, the system uses a plan-based model of narrative comprehension to determine the final content of the story in order to heighten a reader's level of suspense. This paper outlines the various components of the system and describes an empirical evaluation. The evaluation provides strong support for the claim that the system is effective in generating suspenseful stories.

63 citations


Book ChapterDOI
06 Nov 2013
Abstract: In order to tell stories in different voices for different audiences, interactive story systems require: (1) a semantic representation of story structure, and (2) the ability to automatically generate story and dialogue from this semantic representation using some form of Natural Language Generation (nlg). However, there has been limited research on methods for linking story structures to narrative descriptions of scenes and story events. In this paper we present an automatic method for converting from Scheherazade's story intention graph, a semantic representation, to the input required by the personage nlg engine. Using 36 Aesop Fables distributed in DramaBank, a collection of story encodings, we train translation rules on one story and then test these rules by generating text for the remaining 35. The results are measured in terms of the string similarity metrics Levenshtein Distance and BLEU score. The results show that we can generate the 35 stories with correct content: the test set stories on average are close to the output of the Scheherazade realizer, which was customized to this semantic representation. We provide some examples of story variations generated by personage. In future work, we will experiment with measuring the quality of the same stories generated in different voices, and with techniques for making storytelling interactive.

58 citations


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Performance
Metrics
No. of papers from the Conference in previous years
YearPapers
202036
201947
201878
201754
201643
201550