Visual novels are a popular game genre for educational games. However, they often feature pre-authored plot structures that cannot dynamically adjust to the player’s progression through learning objectives. Employing procedural storytelling techniques boosts plot dynamism, but this comes at the cost of needing a larger repository of content (dialogue and images) to support different learning progressions and objectives. In this paper, we present postmortem-style case studies describing the lessons we learned from attempting to integrate large-language models (LLMs) and text-to-image models into the development of an educational visual novel about responsible conduct of research. Specifically, we discuss our experiences employing generative AI in our dialogue, character sprite, and background image creation processes.

NPCs in video games play an essential role in player immersion and maintaining the world’s narrative. NPCs are highlighted in many game genres and systems, but are paramount in faction-based games such as Word of Warcraft, Skyrim, and Fallout 4 [6, 9, 35]. Most faction games use representative or primary characters that rely on heavy scripting to maintain their character believability, while background NPCs that constitute a faction have little to no role in many of these games. Both the experience with these primary NPCs and the experience with background NPCs can be improved by incorporating insights from two sources: character believability research and examining the portrayal of factions in other forms of media. This paper will provide a taxonomy and analysis of current faction systems and suggest methods of improvement.

In this paper, we perform a postmortem of Paradise, a prototype game we built to explore the potential of using a social simulation to structure language model-driven gameplay. We describe our experience using the Ensemble social physics engine and extending its architecture with GPT-3. We detail our resultant hybrid simulation system, in which the simulation state informs generated dialogue, and generated dialogue informs the simulation state. We note that authoring behavior for this system was unmanageable, entailing an unstable balancing act between prompt engineering, the Ensemble social model, and the mapping between the two. We conclude by sharing our reflections on what we learned from the project; we hope this postmortem will be valuable to others researching social physics and language models in games.

Text-to-image models such as DALL-E, Stable Diffusion, and Midjourney have seen a boom in development and adoption in both commercial and hobbyist spaces. This paper is a theoretical analysis aimed at informing the development of games that help improve critical literacy around text-to-image models. It asks: what assumptions and perspectives do text-to-image models have on visual creativity, and how do we bring that out through games? We propose a theory to differentiate between seeing an image through the expression of color, shapes and lines, and seeing an image through the recognition of concepts and ideas. These two ways of seeing are two different ways of orienting the player/user to their visual creativity. While traditional painting mechanics emphasize the former, text-to-image interfaces emphasize the latter. We deploy this perspective to study games with traditional painting interactions and games with text-to-image interactions. This paper hopes to contribute to design both broadly for games about visual creativity, and narrowly for gameplay with text-to-image models — specifically, how the latter fosters a different type of visual creativity than traditional painting interactions.

In creative roleplaying games, game masters take on many roles, including keeping track of the game’s story, remembering past actions, and improvising new content based on player choices and desires. This dynamic storytelling can be quite difficult, particularly in real-time play, and this paper explores how digital tools might be able to assist GMs with elements of this process. In particular, we explore issues that game masters experience in running the GUMSHOE One-2-One system by analyzing posts from the online role playing game community, and discuss the design of a digital tool that helps to address common problems. The resulting tool, Shoelace, helps game masters keep track of story events with a graph-based game world visualization, while also providing creative suggestions using Prolog queries over a database of game information.

The term ‘believability’, when referring to game characters, is used in two incompatible ways: realism, meaning human-like, and character believability as used in the character arts (the illusion of life). The same term being used for two different concepts leads to confusion and inconsistent use of language in research communities. This paper examines the different research areas that cluster under realism and character believability, and then performs a deeper exploration of character believability, focusing on characteristics, examples, and evaluation methodologies.

Tabletop role-playing games require game masters to mediate between the desires of a group of players and the affordances of a mechanically rich game world. In this paper, we explore the potential for large language models like GPT-3 to assist with the improvisational needs of a game master. We build upon Shoelace, a computational assistant for the GUMSHOE One-2-One role-playing framework; using GPT-3, we extend Shoelace to provide dialogue suggestions for non-player characters as well as to highlight relevant game module information. We emphasize the potential for language models to facilitate new role-playing tools and mechanics and suggest that the user experience problems presented by language models and role-playing are still underexplored and unresolved.

This paper presents Neighborly, a customizable, community-scale social simulation engine for procedurally generating settlements of characters for use in research experimentation or entertainment media. Neighborly is a rational reconstruction of Talk of the Town (TotT), an earlier social simulation for emergent narrative focused on simulating small American towns and the townspeople’s lives. Based on Talk of the Town’s previous success as part of the experimental game Bad News, we wanted to reconstruct it as a general-use social simulation authoring tool. In this paper, we delineate the design space of TotT-like social simulation and compare TotT-likes to other academic projects and commercial social simulation games. Finally, we provide an overview of how Neighborly embodies the essence of TotT while offering users a customizable tool for creating community-scale social simulations.

In tabletop roleplaying games (TTRPGs), game masters (GMs) facilitate creating an improvisational shared story, responding in real time to the actions that players take and the things that they want to see in the world. In order to examine the process by which GMs co-create such player-driven narratives, we conduct interviews with GMs about their process preparing for and running TTRPG campaigns. We qualitatively code these interviews in order to synthesize a list of techniques GMs can use to move the story forward. We also compare these interviews to other sources of advice for GMing in sourcebooks and essays. Using the GMing techniques found through this analysis, we discuss insights into the GMing process and how this can be used to inform the design of a computational assistant for GMs.

Existing game description languages (GDLs) aspire to generality, but their focus on the specification of low-level mechanics leaves game generators that target these GDLs in the awkward position of having to invent combinations of mechanics that work well together from scratch. As a result, many existing game generators are good at producing games that contain novel and surprising combinations of mechanics, but bad at generating games that are readily interpretable by players as cultural artifacts. To address this problem, we introduce the concept of a genre-specific game description language (GSGDL): a game description language that deliberately encodes assumptions about a particular genre of games as a cultural form. As a proof of concept, we demonstrate the use of an internal representation of game structure used by the game creation tool GB Studio as a GSGDL for top-down 2D roleplaying games targeting the Game Boy. The use of this GSGDL gives us leverage to rapidly iterate on game generation features targeting a specific game genre and platform; to work with an existing toolchain that offers graphical editing, code generation, and automated play testing; and to more readily generate games that are interpretable by players as examples of a particular cultural form.

To date, the theatricality of videogames has been examined primarily through the lens of performance, a perspective that centers the liveness of theater and identifies the player with the role of the actor. However, another key facet of theatricality—the process of continuous reflective reinterpretation that characterizes theatrical production—has received less attention, despite its apparent applicability to the cyclical nature of many games. We conduct a reading of the narrative roguelike videogame Hades that emphasizes this reinterpretive process, and find that Hades is essentially structured around a sort of “diegetic backstage” that deliberately invites the player into the process of dramatic reinterpretation—leveraging the power of computation to prompt reflection on the game’s core themes and repeated remotivation of the game’s core gameplay. Our reading suggests that videogames, by shortening the reinterpretive loop that characterizes theatrical production and enabling players to experience many iterations of this loop within the comfort of their own home, can unlock a form of the pleasure that the members of a theater production derive from gradually bringing an initially flawed and disharmonious production into harmony.

In many games, NPC-player interactions play a vital role in gameplay. Previous literature has successfully shown how NPC interaction focused on social simulation is an effective means for creating dynamic characters such as in the games Prom Week and Versu. We believe that social simulation is a key element in the creation of complex characters, which is further aided by natural language interaction and knowledge modeling. In this work, we propose an architecture for player-NPC interactions built on top of the Ensemble engine that additionally incorporates chatbots and knowledge modeling technology, with the objective of making craftable and interesting NPCs more easily authorable.

We present Why Are We Like This? (WAWLT), a mixed-initiative, co-creative storytelling game in which two players develop a story transcript by selecting and editing actions to perform and narrativize in an ongoing simulation. In this paper, we lay out the major technical features of WAWLT’s AI architecture—including story sifting via Datalog queries, social simulation, action suggestions, and player-specified but system-understandable author goals—and discuss how these features work together to produce a play experience that facilitates player creativity.

Choice-driven narratives, such as those created through systems like Twine, are a compelling form of interactive storytelling that have been around for many years. But as long as this form has existed, it has grappled with a persistent design problem: consistently presenting choices that feel both effective and relevant. Brute force can achieve the desired effect, but usually at the cost of prohibitively high authorial burden. To tackle this, generative approaches, such as Mawhorter's Dunyazad, facilitate authoring procedural choice content for reuse and recombination. However, many such systems, while successful on technical levels, have yet to to be used to author large enough structures to support a full game, and require a high technical threshold for authors to use. To further development in this space, we present StoryAssembler, an open source generative narrative system that creates dynamic choice-driven narratives. It formed a critical part of Emma's Journey, an interactive narrative game, the initial version of which was collaboratively authored by a team of six writers. In the course of the game's creation, useful authoring patterns and design lessons were learned, as well as techniques that made the system approachable for first-time users.

While there has been work in interactive narrative built using theory and practice from theater, it has mostly focused on the structure of narrative and how a player's interaction with the plot alters that structure. How a player interacts has usually been tied to common game interaction paradigms. There is an understanding that a videogame player exists somewhere between an audience member and a stage actor---but rarely are players allowed to express themselves in a manner similar to an actor. This paper argues that the acting and directing knowledge of theater is a potentially bountiful resource for designing player and NPC interactions. To illustrate this, the paper presents a literature review of theatrical methodology, its existing relationship to games, and a survey of projects in the interactive narrative and character interaction spaces. The chosen theater practices provide a useful basis for a new type of interaction between players and non-player characters. Additionally, particularly when looking at acting practices, their major concerns with the relationship between character and actor provide useful language to describe and further explore the relationship between the player and their avatar. Finally, this paper proposes one possible way of building systems to encourage new modes of play and alter the relationship between designers, systems, and players.

While generative approaches to game design offer great promise, systems can only reliably generate what they can “understand,” which is often represented in a limited, implicit form in hand-crafted evaluation functions or constructive rules. Proceduralist readings, a semiformal approach for interpreting the meaning of a game based on its underlying processes and interactions in conjunction with aesthetic and cultural cues, offer a novel, systematic approach to game understanding. We formalize proceduralist argumentation as a logic program that performs static reasoning over game specifications to derive higher level meanings, as part of Gemini, a bidirectional game analysis and generation system.

Scholars who study games lack many resources and abilities taken for granted by scholars of other forms such as literature. To begin to address this deficiency, this paper presents a basic formalization for different classes of resources associated with game critical practices, and ties those resources to a prototypical system for their reference, generation, and use in game studies arguments. The formalization is focused on three forms of reference: objective reference to game objects, enacted reference to game performances, and internal reference to sub-structures within both. We operationalize our formalization with the Game and Interactive Software Scholarship Toolkit (GISST), a custom suite of tools that manage the reference and creation of game executable data, game performance video recordings, and game executable state from emulated programs. GISST provides tools for ingesting each class of reference and for the easy creation and citation of game play videos and emulated system states. For the last case, GISST allows for embedding citations to running game programs --- in emulation --- inside web browsers, and for their retrieval through URLs from a stable citation database. The goal is to point toward a new class of scholarly support tool for arguments about games and other interactive software that would benefit from the inclusion of audiovisual and executable references.

Many contemporary interactive digital narratives consist of cinematic content that combines performance, sound and dialogue with conventional patterns of player interactions that dictate the story path. The non-linear nature of the content makes applying methods of annotation and analysis currently used in text and film challenging, as any particular experience may differ in significant ways and a player's response may occur at different times in the experience while still applying to a particular event. As a result, most studies approach analyzing player experience using either qualitative methods or quantitative methods alone, and often these studies focus on experimental systems. We developed a coding scheme that captures opportunities and decisions and provides hooks for annotating story content and player affective response. We plan to annotate recorded player traversals of The Wolf Among Us, a choice-based adventure game, incorporating a non-verbal report method, the Sensual Evaluation Instrument [6], guided by a text-based intermediate format that models the game logic. We use David Elson's Story Intention Graph to annotate the story content [2]. The proposed study will be evaluated by whether the responses capture salient story content between different traversals effectively. We describe a proposed baseline method of manually identifying shared story segments and tagging emotional content of scenes.

Game maps are useful for human players, general-game-playing agents, and data-driven procedural content generation. These maps are generally made by hand-assembling manually-created screen-shots of game levels. Besides being tedious and error-prone, this approach requires additional effort for each new game and level to be mapped. The results can still be hard for humans or computational systems to make use of, privileging visual appearance over semantic information. We describe a software system, Mappy, that produces a good approximation of a linked map of rooms given a Nintendo Entertainment System game program and a sequence of button inputs exploring its world. In addition to visual maps, Mappy outputs grids of tiles (and how they change over time), positions of non-tile objects, clusters of similar rooms that might in fact be the same room, and a set of links between these rooms. We believe this is a necessary step towards developing larger corpora of high-quality semantically-annotated maps for PCG via machine learning and other applications.

This paper expands on and refines the theoretical framework of operational logics, which simultaneously addresses how games operate at a procedural level and how games communicate these operations to players. In the years since their introduction, operational logics have been applied in domains ranging from game studies to game generation and game modeling languages. To support these uses and to enable new ones, we resolve some standing ambiguities and provide a catalog of key, fundamental operational logics.

We propose and evaluate a new technique for learning hybrid automata automatically by observing the runtime behavior of a dynamical system.Working from a sequence of continuous state values and predicates about the environment, CHARDA recovers the distinct dynamic modes, learns a model for each mode from a given set of templates, and postulates \textit{causal} guard conditions which trigger transitions between modes.Our main contribution is the use of information-theoretic measures (1)~as a cost function for data segmentation and model selction to penalize over-fitting and (2)~to determine the likely causes of each transition.CHARDA is easily extended with different classes of model templates, fitting methods, or predicates.In our experiments on a complex videogame character, CHARDA successfully discovers a reasonable over-approximation of the character's true behaviors.Our results also compare favorably against recent work in automatically learning probabilistic timed automata in an aircraft domain: CHARDA exactly learns the modes of these simpler automata.

Abstract—This paper presents Comme il Faut (CiF), an artifi-cial intelligence system thatmatches character performances to ap-propriate social context, with the goal of enabling authors to write high-level rules governing expected character behavior in given so-cial situations, rather than specific fixed choice points in a curated narrative structure. CiF models characters with a complex set of traits, feelings, and relationships, who can form intents, take ac-tions, relate to a shared cultural space, and remember and refer to past events. A set of authored rules encoding appropriate be-havior within a specific story world allow these characters to se-lect actions to take (and respond to actions by others) in a manner consistent with their own personal and social concerns as well as a shifting interpersonal context. Through the development and re-lease of PromWeek, a complete game using CiF as its narrative en-gine, we show how the system successfully creates complex narra-tives that are unique for each player and directed by those players’ attempts to make progress towards story goals. We also show how CiF continues to be used in several in-progress interactive experi-ences (Mismanor and IMMERSE), speaking to the utility and flex-ibility of its design. Index Terms—Artificial intelligence, emergent narrative, game design, interactive drama. I.

Scott Turner's Minstrel is considered a landmark story-generation system, cited as an important system in our field's history for the quality of its output. Other influential systems such as Meehan's Tale-Spin have inspired modern successors, but although a few systems have followed Minstrel's case-based approach, none of them use its “imaginative recall” technique. This paper details Skald, a publicly-released rational reconstruction of Minstrel that enables exploration of Turner's work and discovery of new implications for future research. A key finding is a brittleness only hinted at in Turner's publications: the story library, story templates, and the recall system must be tailored to one another for Turner's original system to function. We show that this can be ameliorated through a number of techniques, however, from adding differential costs to transformations to removing the least-successful author-level actions. Another key finding is that Turner's original “boredom” system limited leverage of the story library. An alternative and its results are presented here. What emerges from this work is a different picture of the original Minstrel than that currently present in the literature, as well as a new system, Skald, that sets the stage for future research to explore Turner's ideas for story generation.

Scott Turner's 1993 Minstrel system was a high water mark in story generation, harnessing the concept of imaginative recall to generate creative stories. Using case-based reasoning and an author level planning system, Minstrel models human creative processes. However, the algorithmic and representational commitments made in Minstrel were never subject to principled and quantitative analysis. By rationally reconstructing Minstrel, we are able to investigate Turner's computational model of creativity and learn new lessons about his architecture. We find that Minstrel's original performance was tied to a well-groomed case library, but by modifying several components of the algorithm we can create a more general version which can construct stories using a sparser and less structured case library. Through a rational reconstruction of Minstrel, we both learn new architectural and algorithmic lessons about Minstrel’s computational model of creativity as well as make his architecture available to the contemporary research community for further experimentation.

Goal-driven autonomy (GDA) is a conceptual model for creating an autonomous agent that monitors a set of expectations during plan execution, detects when discrepancies occur, builds explanations for the cause of failures, and formulates new goals to pursue when planning failures arise. While this framework enables the development of agents that can operate in complex and dynamic environments, implementing the logic for each of the subtasks in the model requires substantial domain engineering. We present a method using case-based reasoning and intent recognition in order to build GDA agents that learn from demonstrations. Our approach reduces the amount of domain engineering necessary to implement GDA agents and learns expectations, explanations, and goals from expert demonstrations. We have applied this approach to build an agent for the real-time strategy game StarCraft. Our results show that integrating the GDA conceptual model into the agent greatly improves its win rate.

Prom Week places players in a typical high-school, abuzz with excitement over the upcoming prom. Players indirectly sculpt the social landscape by having these hapless highschoolers engage in social exchanges with each other. The results of these social exchanges are many and varied---ranging from mild fluctuations in respect to characters professing their eternal love for one another---and are informed by over 5,000 sociocultural considerations encoded in first order logic. Through massaging the interpersonal relationships and learning the personal intricacies of the characters, the player can solve a series of social puzzles; such as making the class-nerd the Prom King, or bringing peace between feuding jocks and preppies.

Natural language understanding (NLU) systems are promising alternatives to traditional menu-based dialogue systems more commonly employed in games, yet they remain widely under-explored and under-studied. In this paper, we present the results from a qualitative study we conducted on different versions of an NLU interface, inspired by previous results showing this interface to maximize player presence and engagement. Specifically we introduced different pacing options to an NLU interface by using prompts and pauses, and studied how these different interface approaches changed player behavior and perception. Our results provide important guidelines on how to design NLU systems for games, but their implications go beyond that: We have found further evidence that careful mediation through interface design, by introducing understandable and player-supporting conventions to interactive experiences, can help designers create user experiences in accordance with their end-goals. Furthermore, our results provide insights into the concept of agency, particularly towards a more complete model that emphasizes the importance of audience expectation and understanding in creating a sense of agency.

Some problems in procedural content generation for games involve hard constraints (e.g. that a generated puzzle is necessarily solvable). Common techniques for generator design lack a way to specify crisp (yes/no) constraints on what counts as a valid content artifact and guarantee these constraints are satisfied in the generator's output. In this paper we present two independent implementations of three diverse level design automation tools for the popular online educational game Refraction. All of the systems guarantee key properties of their output. Applying a constraint-focused generator design perspective in depth, we found that even emergent aesthetic style properties were straightforward to directly control. Our results with Refraction provide further concrete evidence for the claim that the expressive power of constraints and the ease with which they can be incorporated into suitably designed generative processes makes them a powerful tool for producing reliably-controllable generators for game content.

Computer role-playing games (CRPGs) have strong narratives, but in general lack interesting and meaningful choices for the player within the story. As a result, the stories are not playable. In this paper we present an existence proof for a new approach to CRPG stories that addresses this, while providing details of our implementation. We designed and created a new playable experience, Mismanor, to test our theories of playable stories. We discuss the design decisions made as well as the details of the CiF-RPG and GrailGM systems used for complex quest generation and story management based on player's traits and the social state of the game world.

Micro-rhetorics are the representational units of meaning that emerge from the rhetorical affordances of videogame mechanics, abstract gameplay patterns, and thematic depiction. This paper explains the concept of micro-rhetorics, how game dynamics can be interpreted, and how designers can make use of game mechanics to express ideas through simple videogames. This theoretical framework is informed by the design of Game-O-Matic, a videogame authoring tool that generates games to represent ideas. It takes a network of basic relationships between actors and assembles simple arcade-style game mechanics into videogames that are able to make arguments and depict ideas.

While game mechanics are a primary focus in game design and game studies, they have been little discussed in the context of introductory game creation and programming environments. But game mechanics are central here as well, with different tools supporting the elements needed for some game mechanics (and genres) but not others. Research suggests many children, especially girls, want to create games based on dynamic relationships, social interactions, and storytelling. But game creation tools aimed at beginners offer no support for game mechanics that would enable such games. This inspires our work on Kodu AI Lab, a set of extensions to Kodu Game Lab, which we are iteratively developing and evaluating with middle school girls. This paper describes our first extensions (attitudes, learning, and fuzzy logic), the principles guiding them (simplicity, understandability, and expressiveness) and the results of our first evaluation. We conclude with our next planned development: extending the "say" command into a game mechanic.

In this paper, we present Prom Week, a social simulation game about the interpersonal lives of a group of high school students in the week leading up to their prom. By starting the design of the game with a theory of social interaction, Prom Week is able to present satisfying stories that reflect the player's choices in a wide possibility space -- two features that rarely accompany one another. This paper reports the design details of how Prom Week utilizes social physics to achieve rich character specificity while maintaining a highly dynamic story space.

Newsgames and artgames, two genres in which designers wish to communicate messages to players, often deploy procedural representation. Understanding these proceduralist games requires special attention to a game's processes as well as how these interact with its theme and aesthetics. In this paper we present a method for proceduralist readings of arcade-like 2D games so that players can determine their range of intended and unintended meanings, critics can assess the strengths and weaknesses of the presented arguments, and designers can identify ways to refine their rhetorical strategies.

Video games are increasingly producing huge datasets available for analysis resulting from players engaging in interactive environments. These datasets enable investigation of individual player behavior at a massive scale, which can lead to reduced production costs and improved player retention. We present an approach for modeling player retention in Madden NFL 11, a commercial football game. Our approach encodes gameplay patterns of specific players as feature vectors and models player retention as a regression problem. By building an accurate model of player retention, we are able to identify which gameplay elements are most influential in maintaining active players. The outcome of our tool is recommendations which will be used to influence the design of future titles in the Madden NFL series.

Procedural content generators for games produce artifacts from a latent design space. This space is often only implicitly defined, an emergent result of the procedures used in the generator. In this paper, we outline an approach to content generation that centers on explicit description of the design space, using domain-independent procedures to produce artifacts from the described space. By concisely capturing a design space as an answer set program, we can rapidly define and expressively sculpt new generators for a variety of game content domains. We walk through the reimplementation of a reference evolutionary content generator in a tutorial example, and review existing applications of answer set programming to generative-content design problems in and outside of a game context.

Tanagra is a mixed-initiative tool for level design, allowing a human and a computer to work together to produce a level for a 2-D platformer. An underlying, reactive level generator ensures that all levels created in the environment are playable, and provides the ability for a human designer to rapidly view many different levels that meet their specifications. The human designer can iteratively refine the level by placing and moving level geometry, as well as through directly manipulating the pacing of the level. This paper presents the design environment, its underlying architecture that integrates reactive planning and numerical constraint solving, and an evaluation of Tanagra's expressive range.

Launchpad is an autonomous level generator that is based on a formal model of 2-D platformer level design. Levels are built out of small segments called “rhythm groups,” which are generated using a two-tiered, grammar-based approach. These segments are pieced together into complete levels that are then rated according to a set of design heuristics. Generation can be controlled using a set of parameters that influence the level pacing and geometry. The approach minimizes the amount of content that must be manually authored: instead of piecing together large segments of a level, Launchpad uses base components that are commonly found in a number of 2-D platformers. Launchpad produces an impressive variety of levels which are all guaranteed to be playable.

What authoring possibilities arise by blending machine and human control of live embodied character experiences? This paper explores two different "behind-the-scenes" roles for human operators during a three-month gallery installation of an embodied character experience. In the Transcription role, human operators type players' spoken utterances; then, algorithms interpret the player's intention, choose from pre-authored dialogue based on local and global narrative contexts, and procedurally animate two embodied characters. In the Discourse role, human operators select from semantic categories to interpret player intention; algorithms use this "discourse act" to automate character dialogue and animation. We compare these two methods of blending control using game logs and interviews, and document how the amateur operators initially resisted having to learn the Discourse version, but eventually preferred having the authorial control it afforded. This paper also outlines a design space for blending machine and human control in live character experiences.

Dialogue systems are central to role-playing games, adventure games, interactive fictions, and some forms of interactive drama and cinema---but we have little empirical evidence about how, or even whether, the design of dialogue system interfaces shapes gameplay experience. In this paper we present the results of a study directly comparing three different dialogue system interfaces implemented over the complete course of a dramatic, story-focused game. We find that, holding the rest of the game steady, changing the dialogue interface produces significant changes in gameplay experience. Further, these changes shape perceptions of the system well beyond the interface and its operation. The changes are also sometimes resonant with, and sometimes at odds with, conventional wisdom about these interface options in the game design and writing communities. Our study compared three interfaces: a sentence selection interface (which appears to maximize story involvement), an abstract response menu interface (which maximized reasoning about the underlying game structures), and a natural language understanding interface (which maximized a sense of presence and engagement with the overall experience). Our full results provide valuable future guidance for those seeking a dialogue interface that is resonant with their gameplay experience goals.

Tanagra is a prototype mixed-initiative design tool for 2D platformer level design, in which a human and computer can work together to produce a level. The human designer can place constraints on a continuously running level generator, in the form of exact geometry placement and manipulation of the level's pacing. The computer then fills in the rest of the level with geometry that guarantees playability, or informs the designer that there is no level that meets their requirements. This paper presents the design of Tanagra, a discussion of the editing operations it provides to the designer, and an evaluation of the expressivity of its generator.

This paper describes an explicit model for how to interpret and create simple 2D games that reasonably communicate messages through a game's representational layer in a manner that is consistent with its processes.A few prominent experimental games (e.g. Kabul Kaboom, Passage) have demonstrated that when the rhetorical implications of a game's processes and its representational layer are in harmony, worthwhile and coherent messages can be communicated. This paper reports the findings of an extensive analysis of Activision's Kaboom! (1981) [1] that explores its rhetorical design space in the service of developing a general method for the interpretation of simple message-driven games. The paper then shows how the application of this method to even a simple game like Kaboom! reveals an unexpected range of coherent potential messages. The paper concludes with a description of a design process and assistant tool that enables those who are not game designers, or even procedurally literate, to create simple games that present editorial and expressive statements. We see this project as a concrete step forward, both analytically and in enabling production, in the field of procedural rhetoric.

Procedural methods have long been used for generation of art assets, but procedural generation of scenarios has lagged behind. In particular, training games for emergency rescue workers would benefit from procedural scenario generation guided by pedagogical goals. In such a game, users could select what skills they wish to train for, and the system would generate a unique level containing the elements necessary to train those skills. In this paper, we present a system that uses HTN planning to generate collapsed structure training scenarios that are both internally consistent and allow the user to train for the desired goals.

Designing videogames involves weaving together systems of rules, called game mechanics, which support and structure compelling player experiences. Thus a significant portion of game design involves reasoning about the effects of different potential game mechanics on player experience. Unlike some design fields, such as architecture and mechanical design, that have CAD tools to support designers in reasoning about and visualizing designs, game designers have no tools for reasoning about and visualizing systems of game mechanics. In this paper we perform a requirements analysis for design-support tool for game design. We develop a proposal in two phases. First, we review the design-support-system and game-design literatures to arrive at a plausible system that helps designers reason about game mechanics and gameplay. We then refine these requirements in a study of three teams of game designers, investigating their current design problems and gauging interest in our tool proposals and reactions to prototype tools. Our study finds that a game design assistant that is able to formally reason about abstract game mechanics would provide significant leverage to designers during multiple stages of the design process.

In current commercial games, there is generally a lack of physical humor; most humor in games is largely linguistic (dialog) and static (hand-authored). In this paper we propose A Cartoon Making Experience (ACME), a system that models physical humor based on the structure of humorous episodes in The Road Runner and Coyote cartoons. Player's are able to interact with ACME by adding and removing objects from the world. Using a hierarchal task network (HTN) planner, the game plans out a gag based on the item attributes as well as the state of the world. In this paper we provide an analysis of the humor in The Road Runner and Coyote cartoons, position ACME in the context of work on computational humor, and describe our preliminary implementation of ACME.

We present a rhythm-based method for the automatic generation of levels for 2D platformers, where the rhythm is that which the player feels with his hands while playing. Levels are created using a grammar-based method: first generating rhythms, then generating geometry based on those rhythms. Generation is constrained by a set of style parameters tweakable by a human designer. The approach also minimizes the amount of content that must be manually authored, instead relying on geometry components that are included in the level designer's tileset and a set of jump types. Our results show that this method produces an impressive variety of levels, all of which are fully playable.

Conversation is an important part of many games, whether it is there to provide information or entertainment. In the current state of commercial game development, almost all conversation is hand-authored. Further, different authoring approaches are used for conversations between non-player characters (typically linear scripting) versus conversations between a non-player character and a human player (typically dialogue trees). In this paper, we present a tool, designed in collaboration with Telltale Games, for creating cocktail party conversations in which characters engage in free-flowing conversations. From an authorial perspective, we start at the hand-authoring side of the spectrum and add system-level support for conversation generation -- our aim is to decrease the authorial burden of creating a conversation while remaining close to existing methods the company's designers are familiar with using.

In many ways, the central problem of ubiquitous computing -- how computational systems can make sense of and respond sensibly to a complex, dynamic environment laden with human meaning -- is identical to that of Artificial Intelligence (AI). Indeed, some of the central challenges that ubicomp currently faces in moving from prototypes that work in restricted environments to the complexity of real-world environments -- e.g. difficulties in scalability, integration, and fully formalizing context -- echo some of the major issues that have challenged AI researchers over the history of their field. In this paper, we explore a key moment in AI's history where researchers grappled directly with these issues, resulting in a variety of novel technical solutions within AI. We critically reflect on six strategies from this history to suggest technical solutions for how to approach the challenge of building real-world, usable solutions in ubicomp today.

We present a longitudinal investigation of Tableau Machine, an intelligent entity that interprets and reflects the lives of occupants in the home. We created Tableau Machine (TM) to explore the parts of home life that are unrelated to accomplishing tasks. Task support for "smart homes" has inspired many researchers in the community. We consider design for experience, an orthogonal dimension to task-centric home life. TM produces abstract visualizations on a large LCD every few minutes, driven by a set of four overhead cameras that capture a sense of the social life of a domestic space. The openness and ambiguity of TM allow for a cycle of co-interpretation with householders. We report on three longitudinal deployments of TM for a period of six weeks. Participant families engaged with TM at the outset to understand how their behaviors were influencing the machine, and, while TM remained puzzling, householders interacted richly with TM and its images. We extract some key design implications for an experience-focused smart home.

Game-design novices increasingly hope to use game-like expression as a way to express content such as opinions and educational material. Existing game-design toolkits such as Game Maker ease the programming burden, bringing the design of small games within the technical reach of low-budget, non-expert groups. The design process itself remains a roadblock, however: It is not at all obvious how to present topics such as political viewpoints or bike safety in a way that makes use of the unique qualities of the interactive game medium. There are no tools to assist in that aspect of the game design process, and as a result virtually all expressive games come from a small number of game studios founded by experts in designing such games. We propose a game-design assistant that acts in a mixed-initiative fashion, helping the author understand the content of her design-in-progress, providing suggestions or automating the process where possible, and even offering the possibility for parts of the game to be dynamically generated at runtime in response to player interaction. We describe a prototype system that interactively helps authors define spaces of games in terms of common-sense constraints on their real-world references, provides support for them to understand and iteratively refine such spaces, and realizes specific games from the spaces as playable mobile-phone games in response to user input.

Current programming languages and software engineering paradigms are proving insufficient for building intelligent multi-agent systems--such as interactive games and narratives--where developers are called upon to write increasingly complex behavior for agents in dynamic environments. A promising solution is to build adaptive systems; that is, to develop software written specifically to adapt to its environment by changing its behavior in response to what it observes in the world. In this paper we describe a new programming language, An Adaptive Behavior Language (A2BL), that implements adaptive programming primitives to support partial programming, a paradigm in which a programmer need only specify the details of behavior known at code-writing time, leaving the run-time system to learn the rest. Partial programming enables programmers to more easily encode software agents that are difficult to write in existing languages that do not offer language-level support for adaptivity. We motivate the use of partial programming with an example agent coded in a cutting-edge, but non-adaptive agent programming language (ABL), and show how A2BL can encode the same agent much more naturally.

In this paper we present the results of a qualitative, empirical study exploring the impact of immersive technologies on presence and engagement, using the interactive drama Façade as the object of study. In this drama, players are situated in a married couple's apartment, and interact primarily through conversation with the characters and manipulation of objects in the space. We present participants' experiences across three different versions of Façade -- augmented reality (AR) and two desktop computing based implementations, one where players communicate using speech and the other using typed keyboard input. Through interviews and observations of players, we find that immersive AR can create an increased sense of presence, confirming generally held expectations. However, we demonstrate that increased presence does not necessarily lead to more engagement. Rather, mediation may be necessary for some players to fully engage with certain interactive media experiences.

Our demonstration presents AR Façade, a phyiscally embodied version of the interactive drama Façade, at the Beall Center in Irvine, CA. In this drama, players are situated in a married couple's apartment, and interact primarily through conversation with the characters and manipulation of objects in the space. Our demonstration will include two versions of the experience - an immersive augmented reality (AR) version and a desktop computing based implementation, where players communicate using typed keyboard input. Our recent study cross media study revealled emperical differences between the versions [Dow et al. 2007]. Through interviews and observations of players, we found that immersive AR can create an increased sense of presence, confirming generally held expectations. However, we learned that increased presence does not necessarily lead to more engagement. Rather, mediation may be necessary for some players to fully engage with certain immersive media experiences.

Information visualization has often focused on providing deep insight for expert user populations and on techniques for amplifying cognition through complicated interactive visual models. This paper proposes a new subdomain for infovis research that complements the focus on analytic tasks and expert use. Instead of work-related and analytically driven infovis, we propose Casual Information Visualization (or Casual Infovis) as a complement to more traditional infovis domains. Traditional infovis systems, techniques, and methods do not easily lend themselves to the broad range of user populations, from expert to novices, or from work tasks to more everyday situations. We propose definitions, perspectives, and research directions for further investigations of this emerging subfield. These perspectives build from ambient information visualization [32], social visualization, and also from artistic work that visualizes information [41]. We seek to provide a perspective on infovis that integrates these research agendas under a coherent vocabulary and framework for design. We enumerate the following contributions. First, we demonstrate how blurry the boundary of infovis is by examining systems that exhibit many of the putative proper ties of infovis systems, but perhaps would not be considered so. Second, we explore the notion of insight and how, instead of a monolithic definition of insight, there may be multiple types, each with particular characteristics. Third, we discuss design challenges for systems intended for casual audiences. Finally we conclude with challenges for system evaluation in this emerging subfield.

This paper presents an argument for including concepts from the social sciences and the arts in the design of robots for intimate social environments. An example of a robot designed as an interactive dining table situated in a restaurant is described and certain aspects of the particular design approach are explained. It is shown how this can help think about ways to integrate robots into cultural spaces.