CHARDA: Causal Hybrid Automata Recovery via Dynamic Analysis

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 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 selection 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.Comment: 7 pages, 2 figures. Accepted for IJCAI 201

Automated Game Design Learning

While general game playing is an active field of research, the learning of game design has tended to be either a secondary goal of such research or it has been solely the domain of humans. We propose a field of research, Automated Game Design Learning (AGDL), with the direct purpose of learning game designs directly through interaction with games in the mode that most people experience games: via play. We detail existing work that touches the edges of this field, describe current successful projects in AGDL and the theoretical foundations that enable them, point to promising applications enabled by AGDL, and discuss next steps for this exciting area of study. The key moves of AGDL are to use game programs as the ultimate source of truth about their own design, and to make these design properties available to other systems and avenues of inquiry.Comment: 8 pages, 2 figures. Accepted for CIG 201

Build It to Understand It: Ludology Meets Narratology in Game Design Space

Michael Mateas (1,3) and Andrew Stern (2,3) (co-authors listed alphabetically) 1 Georgia Institute of Technology 2 InteractiveStory.net, Zoesis 3 grandtextauto.org Building experimental games offers an alternative methodology for researching and understanding games, beyond what can be understood by playing and studying existing games alone. Through a simultaneous process of research, artmaking and product prototyping in the construction of the interactive drama Façade (Mateas and Stern 2000, 2003), new theoretical and design insights into several game studies questions were realized, including in the hotly debated question of ludology vs. narratology. This paper describes some of the ways that building games can inform researchers about what game scholarship should be focused on and why, ways that building games can offer new perspectives on existing forms and genres, and some advantages of building publicly playable games. For some designers and theorists, interactive story worlds are a holy grail of game design (e.g. Murray 1998, Crawford 2004), while for others narrative is antithetical to interactive experiences, destroying the high-agency, procedural potential of games (e.g. Eskelinen 2001, Frasca 2003). Player agency lies at the heart of the tension between games and narrative, and it is precisely here where building experimental, agency-oriented games is especially adept at resolving this tension. A player has agency when she can form intentions with respect to the experience, take action with respect to those intentions, and interpret responses in terms of the action and intentions; i.e., when she has actual, perceptible effects on the game world. Player agency can be further classified into local agency and global agency: local agency means that the player is able to see immediate, clear reactions to her interaction; global agency means that the long-term sequence of events experienced by the player is strongly determined by player interaction. In an interactive narrative, global agency means that what the player does in the moment strongly influences what significant plot points occur in the future. Those who argue against narrative games point to a supposed predetermined or predestined nature of narrative -- that strong narrative structures have complex sequences of cause and effect, complex character relationships and sequences of character interactions. Since player interaction can at any moment disrupt this narrative structure, the only way to maintain the structure is to remove or severely limit the player\u27s ability to affect the structure. This effectively eliminates global agency, forcing the player down a predetermined path. Thus, ludologists argue that narrative must inevitably mean a diminishment in player agency, and should not be used in game design. Furthermore, some ludologists argue that narrative is fundamentally inconsistent with interaction, since for them, narrative refers to a completed temporal structure, while interaction refers to a potential temporal structure (the trace produced by interaction). A pro-story response is that interactive stories shouldn\u27t contain a single completed story line, but rather a potential story space -- the trace of any one player experience carves a particular story trajectory through this space. The ludologist response to this is to flatly claim that such a generative story system is technically impossible, as it would require better-than-human AI to build (Aarseth 1997). The process of building the interactive drama Façade, with the explicit goal to explore new ways to deconstruct the potential events of a dramatic narrative into small grained-size pieces, annotated to allow the system to dynamically mix and sequence the pieces in response to player interaction, has helped us understand that there do in fact exist narrative structures that allow for both local and global agency, that can offer a satisfying dramatic experience for players. Our playable results, albeit in need of further refinement, suggest that the ludologists\u27 assumptions about the compatibility of narrative with interaction, including the technical impossiblity of generative story systems, are overreaching and premature. These results were achievable because the Façade architecture was built to offer authorial affordances for implementing both local and global agency for interactive narrative, without requiring AI-completeness or agents that pass the Turing test. For game studies in general, these results suggest that the authorial affordances of a game\u27s engine and authoring environment are critical for understanding a game\u27s features; game tools and architectures define an authorial space that provides a given balance between authorship and control. In fact, the AI architecture can itself become a design resource for thinking about the game (Mateas 2003). Additionally, there are several advantages from a game studies perspective for pursuing the process of building experimental games as artmaking -- that is, to go beyond thought experiments or minimal closed-door laboratory prototypes, to create reasonably well-polished, publicly playable experiences, that could even serve as commercial product prototypes. First, building completed experiences forces researchers to deal with all of the details that are easy to gloss over when doing thought experiments alone. Building completed games helps one realize that the lack of specificity of generic frameworks, such as Propp\u27s, are of limited utility; in fact, authoring frameworks are needed, not generic story models. Finally, and equally as important, building games may be the most effective or possibly the only way get industry developers to pay attention to academic games research. If academia wants to do more than train future game industry employees, they\u27ll need to build games. Aarseth, E. 1997. Cybertext. Johns Hopkins University Press. Crawford, C. 2004. Chris Crawford on Interactive Storytelling. New Riders. Eskelinen, M. 2001. Towards Computer Game Studies. Siggraph 2001, Art Gallery, Art And Culture Papers: 83-87. Frasca, G. Ludologists Love Stories Too: Notes From A Debate That Never Took Place. DiGRA Level Up 2003, Utrecht. Mateas, M. 2003. Expressive AI: Games and Artificial Intelligence. DiGRA Level Up 2003, Utrecht. Mateas, M. and Stern, A. 2000. Towards Integrating Plot And Character For Interactive Drama. Socially Intelligent Agents: The Human In The Loop, AAAI Symposium, Sea Crest, MA. Mateas, M. and Stern, A. 2003. Integrating Plot, Character And Natural Language Processing in the Interactive Drama Façade. 1st International Conference on Technologies for Interactive Digital Storytelling and Entertainment, Darmstadt. Murray, J. 1997. Hamlet On The Holodeck. MIT Press

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

Artificial and Computational Intelligence in Games (Dagstuhl Seminar 12191)

This report documents the program and the outcomes of Dagstuhl Seminar 12191 "Artificial and Computational Intelligence in Games". The aim for the seminar was to bring together creative experts in an intensive meeting with the common goals of gaining a deeper understanding of various aspects of artificial and computational intelligence in games, to help identify the main challenges in game AI research and the most promising venues to deal with them. This was accomplished mainly by means of workgroups on 14 different topics (ranging from search, learning, and modeling to architectures, narratives, and evaluation), and plenary discussions on the results of the workgroups. This report presents the conclusions that each of the workgroups reached. We also added short descriptions of the few talks that were unrelated to any of the workgroups