Reading

Course reading material will be drawn from the following list of papers. See the course schedule for specific reading assignments.

All papers are available in T-Square

Mobile Alternate Reality Games

[MacVean11] Andrew MacVean, Sanjeet Hajarnis, Brandon Headrick, Aziel Ferguson, Chinmay Barve, Devika Karnik, and Mark O. Riedl. WeQuest: Scalable Alternate Reality Games Through End-User Content Authoring. To appear in the proceedings of the 8th ACM Conference on Advances in Computer Entertainment (ACE), 2011.

Alternate Reality Games (ARGs) are interactive narrative experiences that engage the player by layering a fictional world over the real world. ARG stories are often geo-specific, requiring players to visit specific locations in the world. Con- sequently, ARGs are played infrequently and only by those who live within proximity of the locations that the stories reference. In this paper, we describe an ARG platform, We- Quest, that addresses the geo-specificity limitation through end-user content generation. An authoring tool allows end- users to create new ARG stories that can be executed auto- matically on geo-location aware mobile devices, leading to greater numbers of available stories to be played. An artifi- cial intelligence processed called location translation makes geo-specific ARGs playable anywhere in the world.

[Reed11] Aaron Reed, Ben Samuel, Anne Sullivan, Ricky Grant, April Grow, Justin Lazaro, Jennifer Mahal, Sri Kurniawan, Marilyn Walker, and Noah Wardrip-Fruin. A Step Towards the Future of Role-Playing Games: The SpyFeet Mobile RPG Project. To appear in the proceedings of the 7th Annual Conference on Artificial Intelligence and Interactive Digital Entertainment, 2011.

Meaningful choice has often been identified as a key component in a player’s engagement with an interac- tive narrative, but branching stories require tremendous amounts of hand-authored content, in amounts that in- crease exponentially rather than linearly as more choice points are added. Previous approaches to reducing au- thorial burden for computer RPGs have relied on cre- ating better tools to manage existing unwieldy struc- tures of quests and dialogue trees. We hypothesize that reducing authorial burden and increasing agency are two sides of the same coin, requiring specific advance- ments in two related areas of design and technology research: (1) dynamic story management architecture that represents story events abstractly and allows story elements to be selected and re-ordered in response to player choices, and (2) dynamic dialogue generation to allow a single story event to be revealed differently by different characters and in the context of dynamic rela- tionships between those characters and the player. This paper describes SpyFeet, a playable prototype of a sto- rytelling system designed to test this hypothesis.

[Lim07] M. Y. Lim and R. Aylett. Narrative construction in a mobile tour guide. In Proceedings of the 4th International Conference on Virtual Storytelling, 2007.

Storytelling capabilities are vital aspect of a tour guide. In this paper, we present a mobile tour guide that emulates a real guide's behaviour by presenting stories based on the user's interests, its own interests, its belief and its current memory activation. This research moves away from the concept of a guide that recites facts about places or events towards a guide that utilises improvisational storytelling tech- niques. Contrasting views and personality are achieved with an inclusion of emotional memories containing the guide's ideology and its past ex- periences.

[Stock07] O. Stock, M. Zancanaro, P. Busetta, C. Callaway, A. Kruger, M. Kruppa, T. Kuik, E. Not, and C. Rocchi. Adaptive, intelligent presentation of information for the museum visitor in PEACH. User Modeling and User-Adapted Interaction, 17(3):257-304, 2007.

The study of intelligent user interfaces and user modeling and adaptation is well suited for augmenting educational visits to museums. We have defined a novel integrated framework for museum visits and claim that such a framework is essential in such a vast domain that inherently implies complex interactivity. We found that it requires a significant investment in software and hardware infrastructure, design and implementation of intelligent interfaces, and a systematic and iterative evaluation of the design and functionality of user interfaces, involving actual visitors at every stage. We defined and built a suite of interactive and user-adaptive technologies for museum visitors, which was then evaluated at the Buonconsiglio Castle in Trento, Italy: (1) animated agents that help motivate visitors and focus their attention when necessary, (2) automatically generated, adaptive video documentaries on mobile devices, and (3) automatically generated post-visit summaries that reflect the individual interests of visitors as determined by their behavior and choices during their visit. These components are supported by underlying user modeling and inference mechanisms that allow for adaptivity and personalization. Novel software infrastructure allows for agent connectivity and fusion of multiple positioning data streams in the museum space.We conducted several experiments, focusing on various aspects of PEACH.

[gustafsson06] Anton Gustafsson, John Bichard, Liselott Brunnberg, Oskar Juhlin, Marco Combetto. Believable environments – Generating interactive storytel-ling in vast location-based pervasive games. Proceedings of the 2006 ACM Conference on Advances in Computer Entertainment, 2006.

Generating content into vast areas is a relevant challenge in the field of location-based pervasive games. In this paper, we present a game proto-type that enables children travelling in the back seat of a car to enjoy a narrated experience where gameplay combines with the experience of trav-eling through the road network. The prototype is designed to provide what we refer to as a believ-able environment. We propose four design char-acteristics to persuasively include a journey within a pervasive game. First, the story should refer to geographical objects with their everyday meanings. Second, the game’s scale needs to cover vast areas. Third, the application should provide sequential storytelling to make it fit with the journey experience, and finally it should pro-vide interaction support where players can en-gage in gameplay and interact with the computer in various ways at the same time as they are looking out of the car window. We describe how these requirements have been implemented in the prototype and present an initial performance test.

[Frazier14] Spencer Frazier and Mark O. Riedl. Toward Using Games and Artificial Intelligence to Proactively Sense the Real World. Proceedings of the 50th Convention of the Society for the Study of Artificial Intelligence and Simulation of Behavior (AISB), Symposium on AI and Games, 2014.

Games With a Purpose can enable an intelligent agent to persistently and pervasively sense the real world by by using game players as reconfigurable sensors. We propose a technique whereby an intelligent agent incentivizes players to collect data by translating data collection tasks into a series of quests in a larger narrative arc in a real world MMORPG. In this paper, we define the concept of Proactive Sensing and provide a framework for Game-Based Proactive Sensing that can adapt games and narrative that optimizes for data collection and long-term player engagement. We lay out our initial steps toward a Proactive Sensing Agent that seeks to tag the geo-spatial locations of accessibility and emergency features in the real world using a set of quests in a mobile game called SnaPets.

Quest Generation in Games

[Hullett09] Kenneth Hullett and Michael Mateas. Scenario Generation for Emergency Rescue Training Games. In Proceedings of the Fourth International Conference on the Foundations of Digital Games (FDG 2009).

This paper presents a reliable and efficient approach to pro- cedurally generating level maps based on the self-organization capabilities of cellular automata (CA). A simple CA-based algorithm is evaluated on an innite cave game, generating playable and well-designed tunnel-based maps. The algo- rithm has very low computational cost, permitting realtime content generation, and the proposed map representation provides sufficient exibility with respect to level design.

[Ashmore07] Calvin Ashmore and Michael Nitsche. 2007. The Quest in a Generated World. Proceedings of DiGRA 2007 Conference.

As procedural content becomes a more appealing option for game development, procedurally determined context is necessary to structure and make sense of this content. We find that a useful means to structure content in 3D games is the quest. The task of generating necessary context then becomes one of quest generation. This paper describes how we implemented a basic quest generator based on key and lock puzzles into a procedural game world. It uses notion of quest as spatial progression and discusses the design of the game world and how our quest generator connects to it. Its findings are twofold: on the technical level we managed to implement a highly flexible content and context generator into an existing game engine; one the content level we can trace signs for higher player interest in quest-enhanced procedural game worlds in comparison to unstructured spaces.

[Dormans10] Joris Dormans. (2010). Adventures in level design: generating missions and spaces for action adventure games. Proceedings of the FDG 2010 Workshop on Procedural Content Generation in Games.

This paper investigates strategies to generate levels for action adventure games. This genre relies more strongly on well-designed levels than rule-driven genres such as strategy or roleplaying games for which procedural level generation has been successful in the past. The approach outlined by this paper distinguishes between missions and spaces as two separate structures that need to be generated in two individual steps. It discusses the merits of different types of generative grammars for each individual step in the process.

[Li10] Boyang Li and Mark O. Riedl. An Offline Planning Approach to Game Plotline Adaptation. Proceedings of the 6th Conference on Artificial Intelligence for Interactive Digital Entertainment, Palo Alto, California, 2010.

Role-playing games, and other types of contemporary video games, usually contain a main storyline consisting of several causally related quests. As players have different motivations, tastes and preferences, it can be beneficial to customize game plotlines. In this paper, we present an offline algorithm for adapting human-authored game plotlines for computer roleplaying games to suit the unique needs of individual players, thereby customizing gaming experiences and enhancing replayability. Our approach uses an plan refinement technique based on partial-order planning to (a) optimize the global structure of the plotline according to input from a player model, (b) maintain plotline coherence, and (c) facilitate authorial intent by preserving as much of the original plotline as possible. A theoretical analysis of the authorial leverage and a user study suggest the benefits of this approach.

[Pita07] Pita,, J., Magerko, B. and Brodie, S. TRUE STORY: Dynamically Generated, Contextually Linked Quests in Persistent Systems. FuturePlay, Toronto, ON, 2007.

Massively Multiplayer Online Role-Playing Games (MMORPGs) typically use a handful of static conventions for involving players in stories, such as predefined quest or story paths (a quest or story path is one in which the user experiences a sequence of related quests that must be accomplished in a particular order). Beyond the work done in MMORPGs there has been strong research in designing adaptive approaches to interactive fiction/drama that dynamically author content for users of the interactions [10] [18]. The system architecture presented in this paper, TRUE STORY, is designed to address issues concerning dynamically generated quest or story paths in persistent worlds, such as MMORPGs, for users to engage in more enhanced, interactive and personal experiences. TRUE STORY empowers persistent world designers by offering a truly modular approach for dynamically generating and presenting compelling content that results in user experiences worth telling a story about. The current implementation is set in a game model to demonstrate a dynamic quest generation system built to present users with unique and compelling experiences linked by context to past quests and/or experiences. This is achieved by utilizing history and relationships developed through interaction between world objects and actions.

Story Generation

The ability to generate narrative is of importance to computer systems that wish to use story effectively for entertainment, training, or education. We identify two properties of story – plot coherence and character believability – which play a role in the success of a story. Plot coherence is the perception by audience members that character actions have relevance to the outcome of the story. Character believability is the perception that character actions are motivated by agents' internal beliefs and desires. Unlike conventional planning in which plan goals represent an agent's intended world state, multiagent story planning involves goals that represent the outcome of a story. In order for the plans' actions to appear believable, multi-agent story planners must determine not only how agents' actions achieve a story's goal state, but must also ensure that each agent appears to be acting intentionally. We present a narrative generation planning system for multi-agent stories that is capable of generating narratives with both strong plot coherence and strong character believability. The planning algorithm uses causal reasoning and a simulated intention recognition process to drive plan creation.

[Gervas04] B Díaz-Agudo, P Gervás, F Peinado. (2004). A Case Based Reasoning Approach to Story Plot Generation. In Proc. of the 7 th European Conf. on Case Based Reasoning.

Automatic construction of story plots has always been a longed-for utopian dream in the entertainment industry, especially in the more commercial genres that are fueled by a large number of story plots with only a medium threshold on plot quality, such as TV series or video games. We propose a Knowledge Intensive CBR (KI-CBR) approach to the probem of generating story plots from a case base of existing stories analyzed in terms of Propp functions. A CBR process is defined to generate plots from a user gquery specifying an initial setting for the story, using an ontology to measure the semantical distance between words and structures taking part in the texts.

[Lebowitz84] Lebowitz, M. (1984). Creating characters in a story-telling universe. Poetics, 13, 171-194.

Extended story generation, i.e., the creation of continuing serials, presents difficult and interesting problems for Artificial Intelligence. We present here the first phase of the development of a program, UNIVERSE, that will ultimately tell extended stories. In particular, after descri inb our overall model of story telling, we present a method for creating universes of characters appropriate for extended story generation. This method concentrates on the need to keep story-telling unverses consistent and coherent. We also describe the information that must be maintained for characters and interpersonal relationships, and the use of stereotypical information about people to help motivate trait values. The use of historical events for motivation is also described. Finally, we present an example of a character generated by UNIVERSE.

[Lebowitz85] Lebowitz, M. (1985). Story-telling as planning and learning. Poetics, 14, 483-502.

The generation of extended plots for melodramatic fiction is an interesting task for Artificial Intelligece research, one that requires the application of genralization techniques to carry out fully. UNIVERSE is a story-telling program that uses plan-like units, 'plot fragments', to generate plot outlines. By using a rich library of plot fragments and a well-developed set of characters. UNIVERSE can create a wide range of plot outlines. In this paper we illustrate how UNIVERSE's plot gramgent library is used to create plot outlines and how it might be automatically extended using explanation-based generalization methods. Our methods are based on analysis of a television melodrama, including comparisons of similar stories.

[Meehan81] Meehan, J. (1981). Tale-Spin. In R.C. Schank and C.K. Riesbeck (Eds). Inside Computer Understanding (pp. 197-226). Lawrence Erlbaum Associates.

TALE-SPIN is a program that writes simple stories. It is easily distinguished from any of the "mechanical" devices one can use for writing stories, such as filling in slots in a canned frame. The goal behind the writing of TALE-SPIN was to find out what kinds of knowledge were needed in story generation. the writing of TALE-SPIN embodied the traditional AI cycle of research. Step 1 was to define a theory. Step 2 was to write a program modeling that theory and to add it to the existing system. Step 3 was to run the system and to observe where the model was incorrect or inadequate, thereby identifying the need for some more theory.

[Porteous09] Porteous, J. and Cavazza, M., 2009. Controlling Narrative Generation with Planning Trajectories: the Role of Constraints. International Conference on Interactive Digital Storytelling.

AI planning has featured in a number of Interactive Story- telling prototypes: since narratives can be naturally modelled as a se- quence of actions it has been possible to exploit state of the art plan- ners in the task of narrative generation. However the characteristics of a \good" plan, such as optimality, aren't necessarily the same as those of a \good" narrative, where errors and convoluted sequences may oer more reader interest, so some narrative structuring is required. In our work we have looked at injecting narrative control into plan generation through the use of PDDL3.0 state trajectory constraints which enable us to express narrative control information within the planning repre- sentation. As part of this we have developed an approach to planning with such trajectory constraints. The approach decomposes the problem into a set of smaller subproblems using the temporal orderings described by the constraints and then solves these subproblems incrementally. In this paper we outline our method and present results that illustrate the potential of the approach.

[Swanson08] Reid Swanson and Andrew S. Gordon. Say anything: A massively collaborative open domain story writing companion. In First International Conference on Interactive Digital Storytelling, Erfurt, Germany, November 2008.

Interactive storytelling is an interesting cross-disciplinary area that has importance in research as well as entertainment. In this paper we explore a new area of interactive storytelling that blurs the line between traditional interactive fiction and collaborative writing. We present a system where the user and computer take turns in writing sentences of a fictional narrative. Sentences contributed by the computer are selected from a collection of millions of stories extracted from Internet weblogs. By leveraging the large amounts of personal narrative content available on the web, we show that even with a simple approach our system can produce compelling stories with our users.

[Tearse12] B. Tearse, Mawhorter, P., Mateas, M., and Wardrip-Fruin, N., Lessons Learned From a Rational Reconstruction of Minstrel, Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence, 2012.

In this paper, we introduce Minstrel Remixed, a rational reconstruction of MINSTREL by Scott Turner. In addition to recreating the landmark story generation system for public usage we also introduce a number of modifications that were made during the reconstruction that allow for investigation into the inner workings of the system. Additionally we introduce Minstrel Remixed as a platform for use in Interactive Narrative applications and provide a number of concrete examples.

[Li12] Boyang Li, Stephen Lee-Urban, D. Scott Appling, and Mark O. Riedl. Crowdsourcing Narrative Intelligence. Advances in Cognitive Systems, vol. 2, 2012.

Narrative intelligence is an important part of human cognition, especially in sensemaking and communicating with people. Humans draw on a lifetime of relevant experiences to explain stories, to tell stories, and to help choose the most appropriate actions in real-life settings. Manual authoring the required knowledge presents a significant bottleneck in the creation of systems demonstrating narrative intelligence. In this paper, we describe a novel technique for automatically learning script-like narrative knowledge from crowdsourcing. By leveraging human workers’ collective understanding of social and procedural constructs, we can learn a potentially unlimited range of scripts regarding how real-world situations unfold. We present quantitative evaluations of the learned primitive events and the temporal ordering of events, which suggest we can identify orderings between events with high accuracy.

[Li13] Boyang Li, Stephen Lee-Urban, George Johnston, and Mark O. Riedl. Story Generation with Crowdsourced Plot Graphs. Proceedings of the 27th AAAI Conference on Artificial Intelligence, 2013.

Story generation is the problem of automatically selecting a sequence of events that meet a set of criteria and can be told as a story. Story generation is knowledge-intensive; traditional story generators rely on a priori defined domain models about fictional worlds, including characters, places, and actions that can be performed. Manually authoring the domain models is costly and thus not scalable. We present a novel class of story generation system that can generate stories in an unknown domain. Our system (a) automatically learns a domain model by crowdsourcing a corpus of narrative examples and (b) generates stories by sampling from the space defined by the domain model. A large-scale evaluation shows that stories generated by our system for a previously unknown topic are comparable in quality to simple stories authored by untrained humans.

Interactive Storytelling

[Kelso93] Kelso, Wehyrauch, Bates. 1993. Dramatic Presence. Presence: The Journal of Teleoperators and Virtual Environments, 2(1).

Let us consider the presentation by computers of rich, highly interactive worlds that are inhabited by dynamic and complex characters, and shaped by aesthetically pleasing stories. We shall call this interactive drama, and we believe that it requires strong characters, aesthetic presentation, and long-term dramatic structure. This paper describes an experiment designed to help us understand how to create interactive drama. Three principal questions are addressed. One, how does it feel to be immersed in a dramatic virtual world filled with characters and story? Two, what is required of the characters (actors) in such a virtual world? Three, what is required of the story and its director? We present an introduction to interactive drama, summarize the Oz system designed to create and present such experiences, and describe our experiment in detail. Finally, drawing from the experiment, we suggest several hypotheses about interactive drama.

[Thue07] David Thue, Vadim Bulitko, Marcia Spetch, and Eric Wasylishen. Interactive Storytelling: A Player Modelling Approach. The Third Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE).

In recent years, the fields of Interactive Storytelling and Player Modelling have independently enjoyed increased interest in both academia and the computer games industry. The combination of these technologies, however, remains largely unexplored. In this paper, we present PaSSAGE (Player- Specific Stories via Automatically Generated Events), an interactive storytelling system that uses player modelling to automatically learn a model of the player’s preferred style of play, and then uses that model to dynamically select the content of an interactive story. Results from a user study evaluating the entertainment value of adaptive stories created by our system as well as two fixed, pre-authored stories indicate that automatically adapting a story based on learned player preferences can increase the enjoyment of playing a computer role-playing game for certain types of players.

[Nelson05] Nelson, M. and Mateas, M. (2005). Search-based drama management in the interactive fiction Anchorhead . Proceedings of the First Conference on Artificial Intelligence and Interactive Digital Entertainment.

Drama managers guide a user through a story experience by modifying the experience in reaction to the user's actions. Search-based drama management (SBDM) casts the dramamanagement problem as a search problem: Given a set of plot points, a set of actions the drama manager can take, and an evaluation of story quality, search can be used to optimize the user's experience. SBDM was first investigated by Peter Weyhrauch in 1997, but little explored since. We return to SBDM to investigate algorithmic and authorship issues, including the extension of SBDM to different kinds of stories, especially stories with subplots and multiple endings, and issues of scalability. In this paper we report on experiments applying SBDM to an abstract story search space based on the text-based interactive fiction Anchorhead. We describe the features employed by the story evaluation function, investigate design issues in the selection of a set of drama management actions, and report results for drama managed versus unmanaged stories for a simulated random user.

[Mateas02] Mateas, M. and Stern, A (2002). Architecture, authorial idioms and early observations of the interactive drama Facade. Technical report CMU-CS-02-198, School of Computer Science, Carnegie Mellon University.

Facade is an artificial intelligence-based art/research experiment in electronic narrative - an attempt to move beyond traditional branching or hyper-linked narrative to create a fully-realized, one-act interactive drama. Integrating an interdisciplinary set of artistic practices and artificial intelligence technologies, we are completing a three year collaboration to engineer a novel architecture for supporting emotional, interactive character behavior and drama-managed plot. Within this architecture we are building a dramatically interesting, real-time 3D virtual world inhabited by computer-controlled characters, in which the user experiences a story from a first-person perspective. Facade will be publicly released as a free download in 2003.

[Magerko04] Magerko, B. and Laird, J.E. Mediating the Tension Between Plot and Interaction. AAAI Workshop Series: Challenges in Game Artificial Intelligence, 2004.

When building a story-intensive game, there is always the question of how much freedom to give the player. Give the player too little, and he may feel constrained and disconnected from the character he is controlling. Give him too much freedom, and the progression of the story may lag or stop altogether. This paper focuses on our attempt to find a balance between offering the player a high degree of interaction and providing a story-based experience where the player is a key character. Our approach is embedded in our Interactive Drama Architecture (IDA), which includes an omniscient story director agent who manages the player’s narrative experience. The director agent uses a declarative description of the plot to track the player’s progress, detect deviations from the plot, and make directions to supporting characters in the game. Our director is embedded within a game we have developed, called Haunt 2, which is an extension to the Unreal Tournament engine.

[Riedl08] Mark O. Riedl, Andrew Stern, Don Dini, and Jason Alderman. Dynamic Experience Management in Virtual Worlds for Entertainment, Education, and Training. International Transactions on Systems Science and Applications, Special Issue on Agent Based Systems for Human Learning, vol. 4(2), 2008.

Modern computer systems have the ability to make the storytelling experience interactive by involving a participant or learner as a character in the narrative itself. We present a framework for creating interactive narratives for entertainment, educational, and training purposes based on a type of agent called an experience manager. An experience manager (a generalization of a drama manager) is an intelligent computer agent that manipulates a virtual world to coerce a participant’s experience to conform to a set of provided properties. Our realization of the experience manager automatically generates narrative content in order to adapt to the user’s actions in the virtual world. The experience management framework has been used to develop an interactive version of Little Red Riding Hood and an interactive practice environment called IN-TALE for educating and training cognitive skills such as situation awareness, cultural awareness, leadership, and decisionmaking.

[Yu14] Hong Yu and Mark O. Riedl. Personalized Interactive Narratives via Sequential Recommendation of Plot Points. IEEE Transactions on Computational Intelligence and Artificial Intelligence in Games, vol. 6(2), 2014.

n story-based games or other interactive systems, a drama manager is an omniscient agent that acts to bring about a particular sequence of plot points for the player to experience. Traditionally, the drama manager’s narrative evaluation criteria are solely derived from a human designer. We present a drama manager that learns a model of the player’s storytelling prefer- ences and automatically recommends a narrative experience that is predicted to optimize the player’s experience while conforming to the human designer’s storytelling intentions. Our drama manager is also capable of manipulating the space of narrative trajectories such that the player is more likely to make choices that result in the recommended experience. Our drama man- ager uses a novel algorithm, called Prefix-Based Collaborative Filtering (PBCF), that solves the sequential recommendation problem to find a sequence of plot points that maximizes the player’s rating of his or her experience. We evaluate our drama manager in an interactive storytelling environment based on choose your own adventure novels. Our experiments show that our algorithms can improve the player’s experience over the designer’s storytelling intentions alone and can deliver more personalized experiences than other interactive narrative systems while preserving players’ agency.

[Cavazza02] Cavazza, M., Charles, F., and Mead, S. (2002). Planning Characters' Behaviour in Interactive Storytelling. Journal of Visualization and Computer Animation, 13, 121-131.

In this paper, we describe a method for implementing the behaviour of artificial actors in the context of interactive storytelling. We have developed a fully implemented prototype based on the Unreal Tournament game engine, and carried experiments with a simple sitcom-like scenario. We discuss the central role of artificial actors in interactive storytelling and how real-time generation of their behaviour participates in the creation of a dynamic storyline. We follow previous work describing the behaviour of artificial actors through AI planning formalisms, and adapt it to the context of narrative representation. In this context, the narrative equivalent of a character's behaviour consists in its role. The set of possible roles for a given actor is represented as a Hierarchical Task Network (HTN). The system uses HTN planning to dynamically generate the character roles, by interleaving planning and execution, which supports dynamic interaction between actors, as well as user intervention in the unfolding plot. Finally, we present several examples of short plots and situations generated by the system from the dynamic interaction of artificial actors.

Story Understanding

[Cullingford81] Cullingford. 1981. SAM. In Schank and Riesbeck (Eds.) Inside Computer Understanding: Five Programs Plus Miniatures.

[Wilensky81] Wilensky. 1981. PAM. In Schank and Riesbeck (Eds.) Inside Computer Understanding: Five Programs Plus Miniatures.

[Lehnert82] Lehnert. 1982. Plot Units: A Narrative Summarization Strategy. In Lehnert and Ringle (Eds.) Strategies for Natural Language Processing

[Riloff10] Goyal, A., Riloff, E., Daume III, H. (2010) "Automatically Producing Plot Unit Representations for Narrative Text", Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing (EMNLP 2010).

In the 1980s, plot units were proposed as a conceptual knowledge structure for representing and summarizing narrative stories. Our research explores whether current NLP technology can be used to automatically produce plot unit representations for narrative text. We create a system called AESOP that exploits a variety of existing resources to identify affect states and applies “projection rules” to map the affect states onto the characters in a story. We also use corpus-based techniques to generate a new type of affect knowledge base: verbs that impart positive or negative states onto their patients (e.g., being eaten is an undesirable state, but being fed is a desirable state). We harvest these “patient polarity verbs” from a Web corpus using two techniques: co-occurrence with Evil/Kind Agent patterns, and bootstrapping over conjunctions of verbs. We evaluate the plot unit representations produced by our system on a small collection of Aesop’s fables.

[Chambers08] Nathanael Chambers and Dan Jurafsky. 2008. Unsupervised Learning of Narrative Event Chains. In Proceedings of ACL/HLT 2008.

Hand-coded scripts were used in the 1970-80s as knowledge backbones that enabled inference and other NLP tasks requiring deep semantic knowledge. We propose unsupervised induction of similar schemata called narrative event chains from raw newswire text. A narrative event chain is a partially ordered set of events related by a common protagonist. We describe a three step process to learning narrative event chains. The first uses unsupervised distributional methods to learn narrative relations between events sharing coreferring arguments. Thesecond applies a temporal classifier to partially order the connected events. Finally, the third prunes and clusters self-contained chains from the space of events. We introduce two evaluations: the narrative cloze to evaluate event relatedness, and an order coherence task to evaluate narrative order. We show a 36% improvement over baseline for narrative prediction and 25% for temporal coherence.

[Mueller07] Erik T. Mueller. Modelling Space and Time in Narratives about Restaurants. Literary and Linguistic Computing Vol. 22, No. 1, 2007.

This study investigated the automatic modelling of space and time in narratives involving dining in a restaurant. We built a program that (1) uses information extraction techniques to convert narrative texts into templates containing key information about the dining episodes discussed in the narratives, (2) constructs commonsense reasoning problems from the templates, (3) uses commonsense reasoning and a commonsense knowledge base to build models of the dining episodes, and (4) generates and answers questions by consulting the models. We describe the program and present the results of running it on a corpus of web texts and American literature.

Discourse Generation

[Cheong14] Yun-Gyung Cheong, and R. Michael Young (2014). Suspenser: A Story Generation System for Suspense. IEEE Transactions on Computational Intelligence and Artificial Intelligence in Games, to appear.

Interactive storytelling has been receiving a growing attention from AI and game communities and a number of computational approaches have shown promises in generating stories for games. However, there has been little research on stories evoking specific cognitive and affective responses. The goal of the work we describe here is to develop a system that produces a narrative designed specifically to arouse suspense from its reader. Our approach attempts to create stories that manipulate the reader’s suspense level by elaborating on the story structure that can influence the reader’s narrative comprehension at a specific point in her reading. Adapting theories developed by cognitive psychologists, our approach uses a plan-based model of narrative comprehension to determine the final content of the story in order to manipulate the reader’s suspense. In this article, we describe our system implementation and empirical evaluations to test the efficacy of this system.

[Bae14] Byung-Chull Bae, and R. Michael Young. (2014). A Computational Model of Narrative Generation for Surprise ArousalIEEE Transactions on Computational Intelligence and Artificial Intelligence in Games, vol 6(2).

This paper describes our effort for a planning-based computational model of narrative generation that is designed to elicit surprise in the reader’s mind, making use of two temporal narrative devices: flashback and foreshadowing. In our compu- tational model, flashback provides a backstory to explain what causes a surprising outcome, while foreshadowing gives hints about the surprise before it occurs. Here, we present Prevoyant, a planning-based computational model of surprise arousal in narrative generation, and analyze the effectiveness of Prevoyant. The work here also presents a methodology to evaluate surprise in narrative generation using a planning-based approach based on the cognitive model of surprise causes. The results of the ex- periments that we conducted show strong support that Prevoyant effectively generates a discourse structure for surprise arousal in narrative.

[Moore94] Moore, Paris. 1994. Planning text for advisory dialogues: Capturing intentional, rhetorical and attentional information. Computational Linguistics, 19(4)

To participate in a dialogue a system must be capable of reasoning about its own previous utter- ances. Follow-up questions must be interpreted in the context of the ongoing conversation, and the system's previous contributions form part of this context. Furthermore, if a system is to be able to clarify misunderstood explanations or to elaborate on prior explanations, it must understand what it has conveyed in prior explanations. Previous approaches to generating multisentential texts have relied solely on rhetorical structuring techniques. In this paper, we argue that, to handle explanation dialogues successfully, a discourse model must include information about the intended effect of individual parts of the text on the hearer, as well as how the parts relate to one another rhetorically. We present a text planner that records this information and show how the resulting structure is used to respond appropriately to a follow-up question.

Media Generation

[Mairesse10] Mairesse, F., Walker, M.: Towards personality-based user adaptation: Psycholog- ically informed stylistic language generation. User Modeling and User-Adapted Interaction 20, 227–278 (2010)

Conversation is an essential component of social behavior, one of the primary means by which humans express intentions, beliefs, emotions, attitudes and personality. Thus the development of systems to support natural conversational interaction has been a long term research goal. In natural conversation, humans adapt to one another across many levels of utterance production via processes variously described as linguistic style matching, entrainment, alignment, audience design, and accommodation. A number of recent studies strongly suggest that dialogue systems that adapted to the user in a similar way would be more effective. However, a major research challenge in this area is the ability to dynamically generate user-adaptive utterance variations. As part of a personality-based user adaptation framework, this article describes Personage, a highly parameterizable generator which provides a large number of parameters to support adaptation to a user’s linguistic style. We show how we can systematically apply results from psycholinguistic studies that document the linguistic reflexes of personality, in order to develop models to control Personage’s parameters, and produce utterances matching particular personality profiles. When we evaluate these outputs with human judges, the results indicate that humans perceive the personality of system utterances in the way that the system intended.

[Lin11] G. Lin and Walker, M. A., “All the World’s a Stage: Learning Character Models from Film.”, Conference on Artificial Intelligence and Digital Entertainment. 2011

Many forms of interactive digital entertainment involve interacting with virtual dramatic characters. Our long term goal is to procedurally generate character dialogue behavior that automatically mimics, or blends, the style of existing characters. In this paper, we show how lin- guistic elements in character dialogue can define the style of characters in our RPG SpyFeet. We utilize a cor- pus of 862 film scripts from the IMSDb website, repre- senting 7,400 characters, 664,000 lines of dialogue and 9,599,000 word tokens. We utilize counts of linguistic reflexes that have been used previously for personality or author recognition to discriminate different charac- ter types. With classification experiments, we show that different types of characters can be distinguished at ac- curacies up to 83% over a baseline of 20%. We discuss the characteristics of the learned models and show how they can be used to mimic particular film characters.

[Bares99] Bares, Lester. 1999. Intelligent Multi-shot Visualization Intefaces for Dynamic 3D Worlds. Proceedings of the 1999 International Conference on Intelligent User Interfaces.

In next-generation virtual 3D simulation, training, and entertainment environments, intelligent visualization interfaces must respond to user-specified viewing requests so users can follow salient points of the action and monitor the relative locations of objects. Users should be able to indicate which object(s) to view, how each should be viewed, cinematic style and pace, and how to respond when a single satisfactory view is not possible. When constraints fail, weak constraints can be relaxed or multi-shot solutions can be displayed in sequence or as composite shots with simultaneous viewports. To address these issues, we have developed CONSTRAINTCAM, a real-time camera visualization interface for dynamic 3D worlds. It has been studied in an interactive testbed in which users can issue viewing goals to monitor multiple autonomous characters navigating through a virtual cityscape. CONSTRAINTCAM’s real-time performance in this testbed is encouraging.

[He96] He, Cohen, Salesin. 1996. The Virtual Cinematographer: A Paradigm for Automatic Real-Time Camera Control and Directing. Proceedings of SIGGRAPH '96.

This paper presents a paradigm for automatically generating complete camera specifications for capturing events in virtual 3D environments in real-time. We describe a fully implemented system, called the Virtual Cinematographer, and demonstrate its application in a virtual “party” setting. Cinematographic expertise, in the form of film idioms, is encoded as a set of small hierarchically organized finite state machines. Each idiom is responsible for capturing a particular type of scene, such as three virtual actors conversing or one actor moving across the environment. The idiom selects shot types and the timing of transitions between shots to best communicate events as they unfold. A set of camera modules, shared by the idioms, is responsible for the low-level geometric placement of specific cameras for each shot. The camera modules are also responsible for making subtle changes in the virtual actors’ positions to best frame each shot. In this paper, we discuss some basic heuristics of filmmaking and show how these ideas are encoded in the Virtual Cinematographer.

[Elson07] Elson, Riedl. 2007. A Lightweight Intelligent Virtual Cinematography System for Machinima Production. Proceedings of the 3rd Conference on Artificial Intelligence and Interactive Digital Entertainment

Machinima is a low-cost alternative to full production filmmaking. However, creating quality cinematic visualizations with existing machinima techniques still requires a high degree of talent and effort. We introduce a lightweight artificial intelligence system, Cambot, that can be used to assist in machinima production. Cambot takes a script as input and produces a cinematic visualization. Unlike other virtual cinematography systems, Cambot favors an offline algorithm coupled with an extensible library of specific modular and reusable facets of cinematic knowledge. One of the advantages of this approach to virtual cinematography is a tight coordination between the positions and movements of the camera and the actors.

Virtual Characters

[bates94] Joseph Bates. 1994. The role of emotion in believable agents. Communications of the ACM, 7(37).

There is a notion in the Arts of "believable character." It does not mean an honest or reliable character, but one that provides the illusion of life, thus permitting the audience’s suspension of disbelief.

[Loyall97] A. Bryan Loyall. 1997. Believable Agents: Building Interactive Personalities. Ph.D. Thesis. Technical Report CMU-CS-97-123, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA. May 1997.

[Horswill07] Ian Horswill. 2007. Psychopathology, Narrative, and Cognitive Architecture (or: why AI characters should be just as screwed-up as we are). Proceedings of the AAAI Fall Symposium on Intelligent Narrative Technologies.

Historically, AI research has understandably focused on those aspects of cognition that distinguish humans from other animals – in particular, our capacity for complex problem solving. However, with a few notable exceptions, narratives in popular media generally focus on those aspects of human experience that we share with other social animals: attachment, mating and child rearing, violence, group affiliation, and inter-group and inter-individual conflict. Moreover, the stories we tell often focus on the ways in which these processes break down. In this paper, I will argue that current agent architectures don’t offer particularly good models of these phenomena, and discuss specific phenomena that I think it would be illuminating to understand at a computational level.

[Gratch04] Jonathan Gratch and Stacy Marsella. 2004. A Domain-independent framework for modeling emotion. Journal of Cognitive Systems Research, Volume 5, Issue 4.

In this article, we show how psychological theories of emotion shed light on the interaction between emotion and cognition, and thus can inform the design of human-like autonomous agents that must convey these core aspects of human behavior. We lay out a general computational framework of appraisal and coping as a central organizing principle for such systems. We then discuss a detailed domain-independent model based on this framework, illustrating how it has been applied to the problem of generating behavior for a significant social training application. The model is useful not only for deriving emotional state, but also for informing a number of the behaviors that must be modeled by virtual humans such as facial expressions, dialogue management, planning, reacting, and social understanding. Thus, the work is of potential interest to models of strategic decision-making, action selection, facial animation, and social intelligence.

Automated Journalism

[Allen10] Nicholas D. Allen, John R. Templon, Patrick Summerhays McNally, Larry Birnbaum, Kristian Hammond. (2010). Proceedings of the AAAI Fall Symposium on Computational Models of Narrative

There are certain types of stories that are often told in very structured ways; sports stories or financial reports are two ex- amples. Readers care about these narratives because they are passionately interested in the topic and want to read about the specific details of the event. In other words, they care about the data and want to read a story that presents that data to them. However, in order to be compelling these narratives cannot merely repeat the data, rather they must tell a story from the data. In this paper, we will present a model for data- driven story-telling and discuss StatsMonkey, a system that automatically writes baseball stories from raw baseball game numerical data available online. We will show that a machine can generate interesting, readable stories and that it can make editorial decisions about what aspects of a situation to high- light. Further we will show that a machine can determine in what manner those aspects should be shared.

Narrative Psychology

[Bruner91] Bruner. 1991. The Narrative Construction of Reality. Critical Inquiry, 18(1), 1-21.

[Gerrig93] Gerrig. Experiencing Narrative Worlds. Chapters 1 and 3.

[Green00] Green, Brock. The Role of Transportation in the Persausiveness of Public Narratives. Journal of Personality ad Social Psychology, 79(5), 701-721.

Transportation was proposed as a mechanism whereby narratives can affect beliefs. Defined as absorption into a story, transportation entails imagery, affect, and attentional focus. A transportation scale was developed and validated. Experiment 1 (N = 97) demonstrated that extent of transportation augmented story-consistent beliefs and favorable evaluations of protagonists. Experiment 2 (N = 69) showed that highly transported readers found fewer false notes in a story than less-transported readers. Experiments 3 (N = 274) and 4 (A/ = 258) again replicated the effects of transportation on beliefs and evaluations; in the latter study, transportation was directly manipulated by using processing instructions. Reduced transportation led to reduced story-consistent beliefs and evaluations. The studies also showed that transportation and corresponding beliefs were generally unaffected by labeling a story as fact or as fiction.

[Trabasso84] Trabasso, Secco, Van den Broek. 1984. Causal Cohesion and Story Coherence.

[Graesser94] Graesser, Singer, Trabasso. 1994. Constructing Inferences During Narrative Text Comprehension. Psychological Review, 101(3), 371-395.

The authors describe a constructionist theory that accounts for the knowledge-based inferences that are constructed when readers comprehend narrative text. Readers potentially generate a rich variety of inferences when they construct a referential situation model of what the text is about. The proposed constructionist theory specifies that some, but not all, of this information is constructed under most conditions of comprehension. The distinctive assumptions of the constructionist theory embrace a principle of search (or effort) after meaning. According to this principle, readers attempt to construct a meaning representation that addresses the reader's goals, that is coherent at both local and global levels, and that explains why actions, events, and states are mentioned in the text. This study reviews empirical evidence that addresses this theory and contrasts it with alternative theoretical frameworks.

[Graesser91] Graesser, Lang, Roberts. 1991. Question Answering in the Context of Stories. Journal of Experimental Psychology: General, 120(3), 254-277.

In this study a model of question answering (called QUEST) is tested in the context of short stories. College students first read a story and then judged the quality of answers to questions about episodes in the story. The model could account for the goodness-of-answer judgments and decision latencies for 5 categories of questions: why, how, when, enablement, and consequence. QUEST specifies the information sources that are activated during question answering; the content of each information source is structured according to a theory of knowledge representation. QUEST specifies the convergence processes that dramatically narrow down the set of possible answers (activated from the information sources) to a small set of good answers to a question.