A growing body of work in games research, both generative and analytic, seeks to characterize the relationship between a player’s understanding of an interactive narrative and her options for action within it. This paper provides several definitions that collectively serve as a basis for a model of the user’s comprehension of an unfolding story in a game. Central to this approach, we define the notion of narrative affordance. In essence, a game provides a narrative affordance for some course of action when a player can imagine that course of action as part of a story that completes their current story experience. To define narrative affordance, we draw links from cognitive models of narrative comprehension and a range of research on affordance, which we couple with planning approaches to story and discourse generation. In our approach, we view the creation of an interactive narrative that provides a high degree of agency as a discourse generation problem. We posit that an interactive narrative system must reason about the content and organization of its communication with a player in order to prompt a player’s understanding about the game’s story and her role in it. This paper ends by pointing toward a research direction intended to provide insight into a range of aspects of interactive narrative, including role, genre, choice and agency.
Individuals with high-functioning autism spectrum disorders (HFASD) have very individualistic needs, abilities, and are surrounded by very different social contexts. Consequently, special education and therapeutic interventions often need to be adapted to a particular individual. We are interested in developing systems that can help adolescents with HFASD rehearse and learn social skills with reduced aide from parents, guardians, teachers, and therapists. We describe a social skill learning game that utilizes social scenarios. Because of the individualistic needs and abilities of our target users, we describe ongoing work on AI to assist caregivers with the authoring of tailored social scenarios.
Qualitative analysis of procedurally generated narratives remains a difficult hurdle for most narrative generation tools. Typical analysis involves the use of human studies, rating the quality of the generated narratives against a given set of criteria, a costly and time consuming process. In this paper we integrate a set of features within the ReGEN system which aim to ensure narrative correctness and quality. Correct generation is ensured by performing an analysis of the preconditions and postconditions of each narrative event. Narrative quality is ensured by using an existing set of formal metrics which relate quality to the structure of the narrative to guide narrative generation. This quantitative approach provides an objective means of guaranteeing quality within narrative generation.
Research in intelligent narrative technologies has recently experienced a significant resurgence. As the field matures, devising principled evaluation methodologies will become increasingly important to ensure continued progress. Because of the complexities of narrative phenomena, as well as the inherent subjectivity of narrative experiences, effectively evaluating intelligent narrative technologies poses significant challenges.
Poulakos, Steven (Disney Research Zurich) | Kapadia, Mubbasir (Rutgers University) | Schüpfer, Andrea (ETH Zurich) | Zünd, Fabio (ETH Zurich) | Sumner, Robert W. (Disney Research Zurich and ETH Zurich) | Gross, Markus (Disney Research Zurich and ETH Zurich)
In order to use computational intelligence for automated narrative synthesis, domain knowledge of the story world must be defined, a task which is currently confined to experts. This paper discusses the benefits and tradeoffs between agent-centric and event-centric approaches towards authoring the domain knowledge of story worlds. In an effort to democratize story world creation, we present an accessible graphical platform for content creators and even end users to create their own story worlds, populate it with smart characters and objects, and define narrative events that can be used by existing tools for automated narrative synthesis. We demonstrate the potential of our system by authoring a simple bank robbery story world, and integrate it with existing solutions for event-centric planning to synthesize example digital stories.