Why Are We Like This?: Exploring Writing Mechanics for an AI-Augmented Storytelling Game

Why Are We Like This? (WAWLT) is a playful, co-creative, AI-augmented, improvisational storytelling game in which one or more players explore and influence an ongoing simulation which they then glean for narrative material. It uses the recently developed simulation technology of story sifting (the recognition of microstories in a chronicle of simulation events), via the Felt library, to afford a new kind of playful, social, and creative writing experience. In this paper, we discuss our primary design goals: (1) using computation and interaction design to support casual player creativity, and (2) foregrounding character subjectivity as a driver for socially realistic interpersonal conflict. We further discuss how those design goals informed the system development. In particular, they led to the system features of subjective character reflection on past actions through character-centric sifting patterns, player-facing story sifting tools for querying storyworld state and history, and a set of writing mechanics to interface with the simulation and support playful creative writing. Examples of those writing mechanics include (1) explicit statement of system-understandable author goals, which are used to improve next action recommendations, and (2) free text editing of a malleable, textual transcript seeded by parameterized descriptions of player-selected simulation actions. We found in testing that, even in an incomplete state of development, and even among those who don’t consider themselves fiction writers, WAWLT successfully supports player creativity. We also found that WAWLT affords particularly engaging play and a unique co-creative experience with two players, as opposed to just one

Tabletop Roleplaying Games as Procedural Content Generators

Tabletop roleplaying games (TTRPGs) and procedural content generators can both be understood as systems of rules for producing content. In this paper, we argue that TTRPG design can usefully be viewed as procedural content generator design. We present several case studies linking key concepts from PCG research -- including possibility spaces, expressive range analysis, and generative pipelines -- to key concepts in TTRPG design. We then discuss the implications of these relationships and suggest directions for future work uniting research in TTRPGs and PCG.Comment: 9 pages, 2 figures, FDG Workshop on Procedural Content Generation 202

Narrative Substrates: Reifying and Managing Emergent Narratives in Persistent Game Worlds

International audiencePlayers in modern Massively Multiplayer Online Role-Playing Games progress through ambitiously designed narratives, but have no real influence on the game, since only their characters' data, not the game environment, persists. Although earlier games supported player influence by persisting changes in the world, they relied on players' capacity to form their own stories and lacked guidance for character progression. We explore how persistence and narrative emergence let us build upon players' influence rather than restrict it. We ran four studies and found that players highly value first-time and unique events, and often externalize their experiences to the Web to collaborate and socialize, but unintentionally also disrupt some aspects of in-game play. We introduce Narrative Substrates, a theoretical framework for designing game architec-tures that represent, manage, and persist traces of player activity as unique, interactive content. To illustrate and test the theory, we developed the game We Ride and deployed it as a two-phase technology probe over one year. We identify key benefits and challenges of our approach, and argue that reification of emergent narratives offers new design opportunities for creating truly interactive games

Creativity Support for Story Construction Play Experiences

My research involves the design and development of mixed-initiative AI tools that provide players with creativity support in the context of story construction play experiences, especially those driven by malleable simulations that the player has a chance to help design or configure. To that end, I also study existing storytelling practices within game communities as a way of understanding what a desirable computational creative partner might look like; what features of computational systems tend to facilitate and frustrate creativity in their human partners; and what new creative practices might emerge as we create computational creative partners for new domains

Designing to Support Authorship Play in Emergent Narrative Games

Prior interactive narrative research has extensively investigated the question of how game designers can tell stories through games, but little investigation has been done of how and why players use games to tell stories of their own. This thesis investigates player storytelling practices around emergent narrative games as a form of authorship play. First, we examine existing play practices centered on the authorship of written stories based on play experiences. We find that some players deliberately seek out emergent narrative games as storytelling partners, and argue that this is due in part to the creativity support features common to several games within this genre, which can help players overcome certain barriers to creativity—including fear of the blank canvas, fear of judgment, writer's block, and perfectionism. Second, we present Why Are We Like This? (WAWLT), a mixed-initiative co-creative storytelling game based on design insights gleaned from this analysis. We discuss the AI architecture of WAWLT, focusing especially on how it makes use of story sifting and social simulation technologies to provide players with creativity support, and present the results of preliminary playtesting. Finally, we conclude with some brief discussion of the implications of our work in this design space, including our priorities for future work

Narrative Instruments: AI-Based Playable Media for Storytelling

Creativity has been proclaimed as a grand challenge for research in both artificial intelligence (in the form of computational creativity) and human-computer interaction (in the form of creativity support tools). Storytelling is an exemplary creative domain: stories are complex creative artifacts in which many different facets—including theme, plot, character, and narration—must all be brought into alignment for the story as a whole to succeed. Consequently, the development of intelligent narrative technologies represents an excellent way to improve our understanding of creativity as a computational problem. In this dissertation, I discuss my work on the use of AI to provide plot-level creativity support for creative writing—particularly through the implementation of story sifters, which can interactively or autonomously identify sites of narrative potential within large corpuses of potentially narratable events. By crafting human-playable narrative instruments (systems that can be played to produce narrative, much like musical instruments can be played to produce music) based on story sifting technologies, I illustrate how AI can help players refine vague high-level plot ideas into coherent narrative throughlines—resulting in a new form of playful AI-supported co-creative writing, with design implications for AI-based creativity support tools in a wide variety of creative domains

A Demonstration of Blabrecs, an AI-Based Wordgame

Blabrecs is an AI-based modification to the popular wordgame Scrabble. In Blabrecs, English dictionary words may not be played; instead, players may only play nonsense words that are approved by a classifier trained on a list of English dictionary words. Gameplay therefore revolves around inventing plausibly English-sounding nonsense words and learning how to fool the classifier. In this paper, we briefly introduce our design goals for Blabrecs; describe the process by which Blabrecs was designed; and present two distinct implementations of the game's AI judge

AgentCraft: An Agent-Based Minecraft Settlement Generator

AgentCraft is an entry for the Generative Design in Minecraft (GDMC) AI Settlement Generation Competition, including the optional Chronicle Generation challenge. It makes use of an agent-based simulation to organically produce a plausible settlement and a written history of the settlement’s development. Uniquely, AgentCraft utilizes the HTTP Server version of the competition framework to show the agents constructing the settlement in real time—a visual technique that can’t be achieved with the earlier MCEdit framework. In this paper, we aim to provide a point of reference for future agent-based settlement generators by describing how our competition entry works and discussing the benefits and downsides of the agent-based approach. Additionally, we propose a new optional challenge for the GDMC competition, centering on the development of settlement simulations whose inhabitants can be directly observed or interacted with by the player