@article{ware_young_2016, title={Intentionality and Conflict in The Best Laid Plans Interactive Narrative Virtual Environment}, volume={8}, ISSN={1943-068X 1943-0698}, url={http://dx.doi.org/10.1109/tciaig.2015.2489159}, DOI={10.1109/tciaig.2015.2489159}, abstractNote={In this paper, we present The Best Laid Plans, an interactive narrative adventure game, and the planning technologies used to generate and adapt its story in real time. The game leverages computational models of intentionality and conflict when controlling the non-player characters (NPCs) to ensure they act believably and introduce challenge into the automatically generated narratives. We evaluate the game's ability to generate NPC behaviors that human players recognize as intentional and as conflicting with their plans. We demonstrate that players recognize these phenomena significantly more than in a control with no NPC actions and not significantly different from a control in which NPC actions are defined by a human author.}, number={4}, journal={IEEE Transactions on Computational Intelligence and AI in Games}, publisher={Institute of Electrical and Electronics Engineers (IEEE)}, author={Ware, Stephen G. and Young, R. Michael}, year={2016}, month={Dec}, pages={402–411} }
 @inbook{cavazza_young_2016, place={Singapore}, title={Introduction to Interactive Storytelling}, ISBN={9789814560528}, url={http://dx.doi.org/10.1007/978-981-4560-52-8_55-1}, DOI={10.1007/978-981-4560-52-8_55-1}, booktitle={Handbook of Digital Games and Entertainment Technologies}, publisher={Springer}, author={Cavazza, Marc and Young, R. Michael}, editor={Nakatsu, R. and Rauterberg, M. and Ciancarini, P.Editors}, year={2016}, pages={1–16} }
 @article{cardona-rivera_price_winer_young_2016, title={Question Answering in the Context of Stories Generated by Computers}, volume={4}, journal={Advances in Cognitive Systems}, author={Cardona-Rivera, Rogelio E. and Price, Thomas W. and Winer, David R. and Young, R.Michael}, year={2016}, pages={227–245} }
 @inbook{cavazza_michael_2016, place={Singapore}, title={Section editors for Interactive Narrative: A Systems Approach}, ISBN={978-981-4560-52-8}, booktitle={Handbook of Digital Games and Entertainment Technologies}, publisher={Springer Verlag}, author={Cavazza, Marc and Michael, Young R.}, editor={Nakatsu, Ryohei and Ciancarini, Paolo and Rauterberg, MatthiasEditors}, year={2016} }
 @article{cheong_young_2015, title={Suspenser: A Story Generation System for Suspense}, volume={7}, ISSN={1943-068X 1943-0698}, url={http://dx.doi.org/10.1109/tciaig.2014.2323894}, DOI={10.1109/tciaig.2014.2323894}, abstractNote={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 paper, we describe our system implementation and empirical evaluations to test the efficacy of this system.}, number={1}, journal={IEEE Transactions on Computational Intelligence and AI in Games}, publisher={Institute of Electrical and Electronics Engineers (IEEE)}, author={Cheong, Yun-Gyung and Young, R. Michael}, year={2015}, month={Mar}, pages={39–52} }
 @article{bae_young_2014, title={A Computational Model of Narrative Generation for Surprise Arousal}, volume={6}, ISSN={1943-068X 1943-0698}, url={http://dx.doi.org/10.1109/tciaig.2013.2290330}, DOI={10.1109/tciaig.2013.2290330}, abstractNote={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 computational 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 experiments that we conducted show strong support that Prevoyant effectively generates a discourse structure for surprise arousal in narrative.}, number={2}, journal={IEEE Transactions on Computational Intelligence and AI in Games}, publisher={Institute of Electrical and Electronics Engineers (IEEE)}, author={Bae, Byung-Chull and Young, R. Michael}, year={2014}, month={Jun}, pages={131–143} }
 @article{ware_young_harrison_roberts_2014, title={A Computational Model of Plan-Based Narrative Conflict at the Fabula Level}, volume={6}, ISSN={1943-068X 1943-0698}, url={http://dx.doi.org/10.1109/tciaig.2013.2277051}, DOI={10.1109/tciaig.2013.2277051}, abstractNote={Conflict is an essential element of interesting stories. In this paper, we operationalize a narratological definition of conflict and extend established narrative planning techniques to incorporate this definition. The conflict partial order causal link planning algorithm (CPOCL) allows narrative conflict to arise in a plan while maintaining causal soundness and character believability. We also define seven dimensions of conflict in terms of this algorithm's knowledge representation. The first three-participants, reason, and duration-are discrete values which answer the “who?” “why?” and “when?” questions, respectively. The last four-balance, directness, stakes, and resolution-are continuous values which describe important narrative properties that can be used to select conflicts based on the author's purpose. We also present the results of two empirical studies which validate our operationalizations of these narrative phenomena. Finally, we demonstrate the different kinds of stories which CPOCL can produce based on constraints on the seven dimensions.}, number={3}, journal={IEEE Transactions on Computational Intelligence and AI in Games}, publisher={Institute of Electrical and Electronics Engineers (IEEE)}, author={Ware, Stephen G. and Young, R. Michael and Harrison, Brent and Roberts, David L.}, year={2014}, month={Sep}, pages={271–288} }
 @article{niehaus_young_2014, title={Cognitive models of discourse comprehension for narrative generation}, volume={29}, ISSN={0268-1145 1477-4615}, url={http://dx.doi.org/10.1093/llc/fqu056}, DOI={10.1093/llc/fqu056}, abstractNote={Recent work in the area of narrative generation has sought to develop systems that automatically produce experiences for a user that are understood as stories. Much of this prior work, however, has focused on the structural aspects of narrative rather than the process of narrative comprehension undertaken by readers. Cognitive theories of narrative discourse comprehension define explicit models of a reader’s mental state during reading. These cognitive models are created to test hypotheses and explain empirical results about the comprehension processes of readers. They do not often contain sufficient precision for implementation on a computer, and thus, they are not yet suitable for computational generation purposes. This dissertation employs cognitive models of narrative discourse comprehension to define an explicit computational model of a reader’s comprehension process during reading, predicting aspects of narrative focus and inferencing with precision. This computational model is employed in a narrative discourse generation system to select content from an event log, creating discourses that satisfy comprehension criteria. The results of three experiments are presented and discussed, exhibiting empirical support for the computational reader model and the results of generation. This dissertation makes a number of contributions that advance the state-of-the-art in narrative discourse generation: a formal model of narrative focus, a formal model of online inferencing in narrative, a method of selecting narrative discourse content to satisfy comprehension criteria, and implementation and evaluation of these models.}, number={4}, journal={Literary and Linguistic Computing}, publisher={Oxford University Press (OUP)}, author={Niehaus, James and Young, R. Michael}, year={2014}, month={Oct}, pages={561–582} }
 @article{horswill_montfort_young_2014, title={Guest Editorial: Computational Narrative and Games}, volume={6}, ISSN={1943-068X 1943-0698}, url={http://dx.doi.org/10.1109/tciaig.2014.2325879}, DOI={10.1109/tciaig.2014.2325879}, abstractNote={The eleven articles in this special issue focus on the use of computational modeling in developing the narratives for video programs and online games. Narratives are perceived tob e central to cultures, to the ways people communicate, and, many have argued, to cognition itself. The articles in this issue explore these issues and reports on technologies and computer applications that support narative programming.}, number={2}, journal={IEEE Transactions on Computational Intelligence and AI in Games}, publisher={Institute of Electrical and Electronics Engineers (IEEE)}, author={Horswill, Ian D. and Montfort, Nick and Young, R. Michael}, year={2014}, month={Jun}, pages={93–96} }
 @article{young_ware_cassell_robertson_2014, title={Plans and Planning in Narrative Generation: A Review of Plan-Based Approaches to the Generation of Story, Discourse and Interactivity in Narratives}, volume={17}, number={1-2}, journal={Sprache und Datenverarbeitung}, author={Young, R.Michael and Ware, Stephen and Cassell, Bradley and Robertson, Justus}, year={2014}, pages={41–64} }
 @inbook{riedl_young_2014, title={The Importance of Narrative as an Affective Instructional Strategy}, volume={2}, booktitle={Design Recommendations for Intelligent Tutoring Systems}, publisher={Springer Verlag}, author={Riedl, Mark and Young, R. Michael}, editor={Sottilare, Robert and Graesser, Arthur and Hu, Xiangen and Goldberg, BenjaminEditors}, year={2014}, pages={57–70} }
 @inbook{jhala_young_2011, title={Intelligent Machinima Generation for Visual Storytelling}, ISBN={9781441981875 9781441981882}, url={http://dx.doi.org/10.1007/978-1-4419-8188-2_7}, DOI={10.1007/978-1-4419-8188-2_7}, booktitle={Artificial Intelligence for Computer Games}, publisher={Springer New York}, author={Jhala, Arnav and Young, R. Michael}, year={2011}, pages={151–170} }
 @article{thomas_young_2010, title={Annie: Automated Generation of Adaptive Learner Guidance for Fun Serious Games}, volume={3}, ISSN={1939-1382}, url={http://dx.doi.org/10.1109/tlt.2010.32}, DOI={10.1109/tlt.2010.32}, abstractNote={This paper describes some of the difficulties inherent in building intelligent educational games, specifically the challenge of integrating pedagogy with core game play. We introduce a plan-based knowledge representation that provides a novel framework for infusing the core mechanics of a game with pedagogical content. We describe, in detail, a system that leverages this framework to dynamically adapt a game to individual learners at runtime.}, number={4}, journal={IEEE Transactions on Learning Technologies}, publisher={Institute of Electrical and Electronics Engineers (IEEE)}, author={Thomas, J M and Young, R M}, year={2010}, month={Oct}, pages={329–343} }
 @article{jhala_young_2010, title={Cinematic Visual Discourse: Representation, Generation, and Evaluation}, volume={2}, ISSN={1943-068X 1943-0698}, url={http://dx.doi.org/10.1109/tciaig.2010.2046486}, DOI={10.1109/tciaig.2010.2046486}, abstractNote={In this paper, we present the design, implementation, and evaluation of an end-to-end camera planning system called Darshak. Darshak automatically constructs cinematic narrative discourse of a given story in a 3-D virtual environment. It utilizes a hierarchical partial-order causal link (POCL) planning algorithm to generate narrative plans that contain story events and camera directives for filming them. Dramatic situation patterns, commonly used by writers of fictional narratives, are formalized as communicative plan operators that provide a basis for structuring the cinematic content of the story's visualization. The dramatic patterns are realized through abstract communicative operators that represent operations on a viewer's beliefs about the story and its telling. Camera shot compositions and transitions are defined in this plan-based framework as execution primitives. Darshak's performance is evaluated through a novel user study based on techniques used to evaluate existing cognitive models of narrative comprehension. Initial study reveals significant effect of the choice of visualization strategies on measured viewer comprehension. It further shows significant effect of Darshak's choice of visualization strategy on comprehension.}, number={2}, journal={IEEE Transactions on Computational Intelligence and AI in Games}, publisher={Institute of Electrical and Electronics Engineers (IEEE)}, author={Jhala, Arnav and Young, R Michael}, year={2010}, month={Jun}, pages={69–81} }
 @article{riedl_young_2010, title={Narrative Planning: Balancing Plot and Character}, volume={39}, ISSN={1076-9757}, url={http://dx.doi.org/10.1613/jair.2989}, DOI={10.1613/jair.2989}, abstractNote={Narrative, and in particular storytelling, is an important part of the human experience. Consequently, computational systems that can reason about narrative can be more effective communicators, entertainers, educators, and trainers. One of the central challenges in computational narrative reasoning is narrative generation, the automated creation of meaningful event sequences. There are many factors - logical and aesthetic - that contribute to the success of a narrative artifact. Central to this success is its understandability. We argue that the following two attributes of narratives are universal: (a) the logical causal progression of plot, and (b) character believability. Character believability is the perception by the audience that the actions performed by characters do not negatively impact the audience's suspension of disbelief. Specifically, characters must be perceived by the audience to be intentional agents. In this article, we explore the use of refinement search as a technique for solving the narrative generation problem - to find a sound and believable sequence of character actions that transforms an initial world state into a world state in which goal propositions hold. We describe a novel refinement search planning algorithm - the Intent-based Partial Order Causal Link (IPOCL) planner - that, in addition to creating causally sound plot progression, reasons about character intentionality by identifying possible character goals that explain their actions and creating plan structures that explain why those characters commit to their goals. We present the results of an empirical evaluation that demonstrates that narrative plans generated by the IPOCL algorithm support audience comprehension of character intentions better than plans generated by conventional partial-order planners.}, journal={Journal of Artificial Intelligence Research}, publisher={AI Access Foundation}, author={Riedl, M. O. and Young, R. M.}, year={2010}, month={Sep}, pages={217–268} }
 @article{harris_young_2009, title={Proactive Mediation in Plan-Based Narrative Environments}, volume={1}, ISSN={1943-068X 1943-0698}, url={http://dx.doi.org/10.1109/tciaig.2009.2035610}, DOI={10.1109/tciaig.2009.2035610}, abstractNote={In interactive plan-based narrative environments, users' actions must be monitored to ensure that conditions necessary for the execution of narrative plans are not compromised. In the Zocalo system, management of user actions has been performed on a reactionary basis by a process called mediation. In this paper, we describe an extension to this approach, <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">proactive mediation</i> , which calculates responses to user input in an anticipatory manner. A proactive mediation module accepts as input a plan describing the actions being performed by the user (generated by a plan recognition system) and identifies portions of that plan that jeopardize the causal structure of the overall narrative. Once these portions are identified, proactive mediation generates modifications to the narrative plan structure that avoid the unwanted interaction between user and story. This extension to the original mediation algorithm provides more responses to a user's actions and generates responses that are tailored to the user's activity.}, number={3}, journal={IEEE Transactions on Computational Intelligence and AI in Games}, publisher={Institute of Electrical and Electronics Engineers (IEEE)}, author={Harris, J. and Young, R.M.}, year={2009}, month={Sep}, pages={233–244} }
 @article{young_2007, title={Story and discourse: A bipartite model of narrative generation in virtual worlds}, volume={8}, ISSN={1572-0373 1572-0381}, url={http://dx.doi.org/10.1075/is.8.2.02you}, DOI={10.1075/is.8.2.02you}, abstractNote={In this paper, we set out a basic approach to the modeling of narrative in interactive virtual worlds. This approach adopts a bipartite model taken from narrative theory, in which narrative is composed of story and discourse. In our approach, story elements — plot and character — are defined in terms of plans that drive the dynamics of a virtual environment. Discourse elements — the narrative’s communicative actions — are defined in terms of discourse plans whose communicative goals include conveying the story world plan’s structure. To ground the model in computational terms, we provide examples from research under way in the Liquid Narrative Group involving the design of the Mimesis system, an architecture for intelligent interactive narrative incorporating concepts from artificial intelligence, narrative theory, cognitive psychology and computational linguistics.}, number={2}, journal={Interaction Studies}, publisher={John Benjamins Publishing Company}, author={Young, R. Michael}, year={2007}, pages={177–208} }
 @inbook{young_2006, place={Mahwah, New Jersey}, title={Cognitive and Computational Models in Interactive Narratives}, ISBN={9781410617088}, booktitle={Cognitive Systems: Human Cognitive Models in Systems Design}, publisher={Lawrence Erlbaum}, author={Young, R.Michael}, editor={Forsythe, Chris and Bernard, Michael L. and Goldsmith, Timothy E.Editors}, year={2006}, pages={213–235} }
 @article{riedl_young_2006, title={From linear story generation to branching story graphs}, volume={26}, ISSN={0272-1716}, url={http://dx.doi.org/10.1109/mcg.2006.56}, DOI={10.1109/mcg.2006.56}, abstractNote={Narrative intelligence refers to the ability - human or computer - to organize experience into narrative. Recently, researchers have applied narrative intelligence to create interactive narrative systems, virtual worlds in which a story unfolds and the user is considered a character in the story, able to interact with elements and other characters in the virtual world. The standard approach to incorporating storytelling into a computer system is to script a story at design time. However, this approach limits the computer system's ability to adapt to the user's preferences and abilities. The alternative approach is to generate stories dynamically or on a per-session basis (one story per time the system is engaged). Narrative generation is a process that involves the selection, ordering, and presentation through discourse of narrative content. A system that can generate stories can adapt narrative to the user's preferences and abilities, has expanded replay value, and can interact with users in ways that system designers didn't initially envision}, number={3}, journal={IEEE Computer Graphics and Applications}, publisher={Institute of Electrical and Electronics Engineers (IEEE)}, author={Riedl, M.O. and Young, R.M.}, year={2006}, month={May}, pages={23–31} }
 @article{riedl_young_2006, title={Story planning as exploratory creativity: Techniques for expanding the narrative search space}, volume={24}, ISSN={0288-3635 1882-7055}, url={http://dx.doi.org/10.1007/bf03037337}, DOI={10.1007/bf03037337}, number={3}, journal={New Generation Computing}, publisher={Springer Science and Business Media LLC}, author={Riedl, Mark O. and Young, R. Michael}, year={2006}, month={Sep}, pages={303–323} }
 @inbook{michael young_2005, place={Boca Raton, FL}, series={Chapman & Hall/CRC computer and information science series}, title={Internet-Based Games}, ISBN={9781584883814 9781466526907}, ISSN={2154-4573}, url={http://dx.doi.org/10.1201/9780203507223.ch11}, DOI={10.1201/9780203507223.ch11}, booktitle={The Practical Handbook of Internet Computing}, publisher={Chapman and Hall/CRC}, author={Michael Young, R}, editor={Singh, Munindar P.Editor}, year={2005}, collection={Chapman & Hall/CRC computer and information science series} }
 @article{young_riedl_branly_jhala_martin_saretto_2004, title={An architecture for integrating plan-based behavior generation with interactive game environments}, volume={1}, number={1}, journal={The Journal of Game Development}, author={Young, R.Michael and Riedl, Mark and Branly, Mark and Jhala, Arnav and Martin, R.J. and Saretto, C.J.}, year={2004}, month={Mar}, pages={51–70} }
 @inbook{young_2002, place={Boston, MA}, title={The Cooperative Contract in Interactive Entertainment}, volume={3}, ISBN={9780306473739 9781402070570}, DOI={10.1007/0-306-47373-9_28}, abstractNote={Interactions with computer games demonstrate many of the same social and communicative c onventions that are seen in conversations between people. I propose that a co-operative contract exists between computer game players and game systems (or their designers) that licenses both the game players’ and the game designers’ understanding of what components of the game mean. As computer and console games become more story-oriented and interactivity within these games becomes more sophisticated, this co-operative contract will become even more central to the e njoyment of a game experience. This chapter describes the nature of the co-operative contract and one way that we are designing game systems to leverage the contract to create more compelling experiences.}, booktitle={Socially Intelligent Agents, Multiagent Systems, Artificial Societies, and Simulated Organizations}, publisher={Springer}, author={Young, R. Michael}, editor={Dautenhahm, Kerstin and Bond, Alan and Canamero, Lola and Edmonds, BruceEditors}, year={2002}, pages={229–234} }
 @article{young_1999, title={Using Grice's maxim of Quantity to select the content of plan descriptions}, volume={115}, ISSN={0004-3702}, url={http://dx.doi.org/10.1016/s0004-3702(99)00082-x}, DOI={10.1016/s0004-3702(99)00082-x}, abstractNote={Intelligent systems are often called upon to form plans that direct their own or other agents' activities. For these systems, the ability to describe plans to people in natural ways is an essential aspect of their interface. In this paper, I present the Cooperative Plan Identification (CPI) architecture, a computational model that generates concise, effective textual descriptions of plans. In this model, speakers and hearers cooperate with one another in their communication about a plan. A hearer interprets a concise plan description by filling in the missing detail using plan reasoning. A cooperative speaker selects the content of a plan description based on his expectation that the hearer is able to complete the description in much the same way that a planning system completes a partial plan. The architecture has been empirically evaluated in an experiment, also described here, in which subjects following instructions produced by the CPI architecture performed their tasks with fewer execution errors and achieved a higher percentage of their tasks' goals than did subjects following instructions produced by alternative methods.}, number={2}, journal={Artificial Intelligence}, publisher={Elsevier BV}, author={Young, R.Michael}, year={1999}, month={Dec}, pages={215–256} }
 @article{button_young_ahart_1986, title={A framework for troubleshooting asynchronous data communications links}, volume={31}, number={11}, journal={Hewlett-Packard Journal}, author={Button, Brian and Young, Michael R. and Ahart, Diane M.}, year={1986}, pages={41–47} }