Ben A. Kybartas

A Survey on Story Generation Techniques for Authoring Computational Narratives

Computers are often used as tools to design, implement, and even visualize a variety of narrative forms. Many researchers and artists are now further attempting to engage the computer actively throughout the development of the narrative itself. Any form of computational narrative authoring is at some level always mixed-initiative , meaning that the processing capabilities of the computer are utilized with a varying degree to automate certain features of the authoring process. We structure this survey by focusing on two key components of stories, plot and space, and more specifically the degree to which these are either automated by the computer or authored manually. By examining the successes of existing research, we identify potential new research directions in the field of computational narrative. We also identify the advantages of developing a standard model of narrative to allow for collaboration between plot and space automation techniques. This would likely benefit the field of automated space generation with the strengths in the field of automated plot generation.

Tracery: An Author-Focused Generative Text Tool

New communities of generative text practitioners are flourishing in novel expressive mediums like Twitterbots and Twine as well as the existing practices of Interactive Fiction. However, there are not yet reusable and extensible generative text tools that work for the needs of these communities. Tracery is an author-focused generative text tool, intended to be used by novice and expert authors, and designed to support generative text creation in these growing communities, and future ones. We identify the design considerations necessary to serve these new generative text authors, like data portability, modular design, and additive authoring, and illustrate how these considerations informed the design of the Tracery language. We also present illustrative case studies of existing projects that use Tracery as part of the art creation process.

A Semantic Foundation for Mixed-Initiative Computational Storytelling

In mixed-initiative computational storytelling, stories are authored using a given vocabulary that must be understood by both author and computer. In practice, this vocabulary is manually authored ad-hoc, and prone to errors and consistency problems. What is missing is a generic, rich semantic vocabulary that is reusable in different applications and effectively supportive of advanced narrative reasoning and generation. We propose the integration of lexical semantics and commonsense knowledge and we present GluNet, a flexible, open-source, and generic knowledge-base that seamlessly integrates a variety of lexical databases and facilitates commonsense reasoning. Advantages of this approach are illustrated by means of two prototype applications, which make extensive use of the GluNet vocabulary to reason about and manipulate a coauthored narrative. GluNet aims to promote interoperability of narrative generation systems and sharing corpus data between fields of computational narrative.

An audio game for training navigation skills of blind children

Training blind children to use audio-based navigation is a demanding and risky task, as children can walk into objects and hurt themselves. Furthermore, training outdoors is dangerous due to traffic, noise and weather conditions. Having a controlled indoor environment is safer but not always available. To tackle this problem, we developed an audio-based computer game, Legend of Iris (LOI), specifically designed to train navigation skills. The game is a 3D exploration game, which uses the headtracking capabilities of the Oculus Rift to create an immersive experience, and the new sound libraries AstoundSound and Phonon3D, to generate an accurate and realistic soundscape. These libraries use a head-related transfer function, allowing the player to localize the audio source in 3D space. The design of LOI involved selecting sounds that are easily recognizable to provide cues to blind people playing the game. A subset of these cues were incorporated into the game. To verify the effectiveness of the game in developing audio orientation and navigation skills, we performed a preliminary qualitative experiment with blind children in a dedicated school. LOI scored high in terms of accuracy and immersion, but a larger test is required to make statistical conclusions.

Analysis of ReGEN as a Graph-Rewriting System for Quest Generation

Using procedural narrative generation in video games provides a flexible way to extend game play and provide more depth to the game world at low cost to the developers. Current examples of narrative generation in commercial games, however, tend to be simplistic, resulting in repetitive and uninteresting stories. In this paper, we develop a system for narrative generation using a context-aware graph-rewriting framework. We use a graph representation of the game world to create narratives which reflect and modify the current world state. Using a novel set of metrics to evaluate narrative quality, we validate our approach by comparing our generated narratives to other procedurally generated stories, as well as to authored narratives from commercially successful and critically praised games. The results show that our narratives compare favorably to the authored narratives. Our metrics provide a new approach to narrative analysis, and our system provides a unique and practical approach to story generation.

Taxi trouble: communication is key

We present the Android game Taxi Trouble, an interactive, competitive and collaborative multi-player game focusing on stimulating social interaction, effective communication and entertaining groups of four to eight people for a short timeframe.

BloxAR: augment your social life!

Many people who own a smartphone spend a large amount of time playing mobile games. Despite the technological capabilities and social potential of these devices, the majority of mobile games make limited use of available technologies and contain little or no multiplayer elements. BloxAR is an augmented reality mobile game that aims to provide a fun and engaging social experience. In this game, players compete in teams to be the first to build a virtual block structure within a set time. Play consists of physically exploring the structure in an augmented reality environment, building the structure by placing blocks and cooperating with teammates to combine blocks together.

Subject and Subjectivity: A Conversational Game Using Possible Worlds

We present Subject and Subjectivity, an exploratory conversational game where players are tasked with matching their friends with the ideal bachelor. The system uses a modal logic approach to modeling the narrative, based upon Marie-Laure Ryan’s possible worlds model for narrative [1]. The dialogue occurs in real-time and consists of navigating each character’s multiple and often conflicting world views. The system allows flexible character authoring, demonstrated by having the demo be playable with either hand-authored or procedurally generated characters. The demo serves as an early experiment into the use of possible worlds logic for interactive storytelling and dialogue systems.