Reading List

Below is a list of important publications for NIL members.

Narrative Theory
Cognitive Science
Artificial Intelligence
Computational Models of Narrative
Intelligent Tutoring and Training

Narrative Theory

General Information

Vladimir Iakovlevich Propp. Morphology of the folktale. Trans. Laurence Scott, 1968. University of Texas Press.
Propp's structural analysis of Russian folktales is usually considered the beginning of narratology.
John R. Searle. Minds, brains, and programs. Behavioral and Brain Sciences, vol. 3, num. 03, pp. 417-424, 1980. Cambridge University Press.
Searle's controversial Chinese Room argument against Strong AI.
David Herman, Manfred Jahn, Marie-Laure Ryan. Routledge encyclopedia of narrative theory. 2005. Routledge.
Defines common narratology terms.
H. Porter Abbott. The Cambridge introduction to narrative. 2008. Cambridge University Press.
An easy to read and helpful introduction to narratology.
William Indick. Psychology for screenwriters. 2004. Michael Wiese Productions.
An insightful application of classical psychological theories to narrative structure.
Janet Horowitz Murray. Hamlet on the holodeck: the future of narrative in cyberspace. 1997. Simon and Schuster.
A vision for the future of storytelling.
Michael Mateas, Phoebe Sengers. Narrative intelligence. In Proceedings of the AAAI Fall Symposium on Narrative Intelligence, pp. 1-10, 1999.
A survey of narratology and its influences on computational models of narrative.
Marc Cavazza, David Pizzi. Narratology for interactive storytelling: a critical introduction. In International Conference on Technologies for Interactive Digital Storytelling and Entertainment, pp. 72-83, 2006.
A survey of narratology terms for interactive storytelling researchers.

Interactive Narrative

Michael Mateas. A preliminary poetics for interactive drama and games. Digital Creativity, vol. 12, num. 3, pp. 140-152, 2001. Taylor & Francis.
Artistic and analytical considerations for the creation of interactive narratives.
Nicolas Szilas. Requirements for computational models of interactive narrative. In Proceedings of the AAAI Fall Symposium on Computational Models of Narrative, pp. 62-68, 2010.
Interactive narratives are fundamentally different than static narratives and computational models need to account for this.

Agency

Noah Wardrip-Fruin, Michael Mateas, Steven Dow, Serdar Sali. Agency reconsidered. In Proceedings of the Digital Games Research Association, 2009.
A survey of work on agency.
See also: Measuring presence in virtual environments: a presence questionnaire.
Matthew William Fendt, Brent Harrison, Stephen G. Ware, Rogelio E. Cardona-Rivera, David L. Roberts. Achieving the illusion of agency. In Proceedings of the 5th International Conference on Interactive Digital Storytelling, pp. 114-125, 2012. (awarded Best Paper)
Demonstrates that feedback can create a sense of agency in a low-agency story.
Rogelio E. Cardona-Rivera, Justus Robertson, Stephen G. Ware, Brent Harrison, David L. Roberts, R. Michael Young. Foreseeing meaningful choices. In Proceedings of the 10th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, pp. 9-15, 2014.
Demonstrates that EISM indices can be used to predict high agency choices in interactive narratives.

Possible Worlds

Jerome S. Bruner. Actual minds, possible worlds. 1986. Harvard University Press.
A formulation of narrative theory in terms of possible worlds.
Marie-Laure Ryan. Possible worlds, artificial intelligence, and narrative theory. 1991. Indiana University Press.
An analysis of narrative as possible worlds from an author with a background in both narratology and computer science.
Richard J. Gerrig, William G. Wenzel. The role of inferences in narrative experiences. In Inferences during reading, Eds. Edward J. O'Brien, Anne E. Cook, Robert F. Lorch Jr, pp. 362-385, 2015. Cambridge University Press.
A discussion of the kinds of inferences readers make when experiencing a narrative.

Cognitive Science

General Information

Fritz Heider, Marianne Simmel. An experimental study of apparent behavior. The American Journal of Psychology, vol. 57, num. 2, pp. 243-259, 1944.
A famous experiment where subjects attributed minds to abstract geomatric shapes moving around, which demonstrates our innate tendency to narrativize sensory input.
Jerome Bruner. The narrative construction of reality. Critical inquiry, pp. 1-21, 1991.
Narrative is one of the fundamental means by which we understand the world.
Richard J. Gerrig. Experiencing narrative worlds: on the psychological activities of reading. 1993. Yale University Press.
An introduction to and survey of cognitive science for narrative.
See also: Psychology for screenwriters.
Rogelio E. Cardona-Rivera, R. Michael Young. Desiderata for a computational model of human online narrative sensemaking. In Working notes of the 2019 AAAI Spring Symposium on Story-enabled Intelligence, 2019.
An introduction to several cognitive science theories that are relevant to AI storytelling and story understanding.

QUEST Framework

Arthur C. Graesser, Sallie E. Gordon, Lawrence E. Brainerd. QUEST: A model of question answering. Computers & Mathematics with Applications, vol. 23, num. 6, pp. 733-745, 1992. Elsevier.
Describes QUEST, a empirical method for evaluating how humans answer questions after reading stories.
Arthur C. Graesser, Paul J. Byrne, Michael L. Behrens. Answering questions about information in databases. Questions and Information Systems, pp. 229-252, 1992. Lawrence Erlbaum.
Another survey of QUEST.
David B. Christian, R. Michael Young. Comparing cognitive and computational models of narrative structure. In Proceedings of the 19th National Conference of the American Association for Artificial Intelligence, pp. 385-390, 2004.
A mapping of some QUEST structures onto POCL planning data structures.
Rogelio E. Cardona-Rivera, Thomason Price, David Winer, R. Michael Young. Question answering in the context of stories generated by computers. Advances in Cognitive Systems, vol. 4, pp. 227-245, 2016.
Uses QUEST to answer questions about stories generated by a planning algorithm.
Rachelyn Farrell, Scott Robertson, Stephen G. Ware. Asking hypothetical questions about stories using QUEST. In Proceedings of the 9th International Conference on Interactive Digital Storytelling, pp. 136-146, 2016.
Demonstrates that readers can reason about other possible worlds when answering QUEST-style questions.

Event-Indexing Situation Models

Rolf A. Zwaan, Gabriel A. Radvansky. Situation models in language comprehension and memory. Psychological Bulletin, vol. 123, num. 2, p. 162, 1998. American Psychological Association.
The EISM (Event-Indexing Situation Model) describes various dimensions that can predict how readily humans recall past events in a narrative.
Rogelio E. Cardona-Rivera, Bradley A. Cassell, Stephen G. Ware, R. Michael Young. Indexter: a computational model of the Event-Indexing Situation Model for characterizing narratives. In Proceedings of the 3rd workshop on Computational Models of Narrative, pp. 34-43, 2012. (awarded Best Student Paper on a Cognitive Science Topic)
A mapping for some EISM indices onto POCL planning data structures.
See also: Foreseeing meaningful choices.
Rachelyn Farrell, Stephen G. Ware, Lewis J. Baker. Manipulating narrative salience in interactive stories using Indexter's Pairwise Event Salience Hypothesis. IEEE Transactions on Games, vol. 12, num. 1, pp. 74-85, 2020.
A summary of three key Indexter results: it measures the salience of past events, predicts the salience of future events, and can be used to generate interactive stories that influence player choices.

Planning and Causality in Narrative

Tom Trabasso, Paul Van Den Broek. Causal thinking and the representation of narrative events. Journal of memory and language, vol. 24, num. 5, pp. 612-630, 1985.
Describes several studies of how the causal relationships between events affect memory, recall, and the importance of events when reading a narrative.
Tom Trabasso, Linda L Sperry. Causal relatedness and importance of story events. Journal of Memory and language, vol. 24, num. 5, pp. 595-611, 1985.
Events that are parts of causal chains in stories are perceived to be more important.
Richard J. Gerrig, Allan B. I. Bernardo. Readers as problem-solvers in the experience of suspense. Poetics, vol. 22, num. 6, pp. 459-472, 1994. Elsevier.
Suspense is correlated to the perceived number of solutions available to a character who is in danger.

Presence and Engagement

Bob G. Witmer, Michael J. Singer. Measuring presence in virtual environments: a presence questionnaire. Presence: Teleoperators and Virtual Environments, vol. 7, num. 3, pp. 225-240, 1998. MIT Press.
Describes two questionnaires used to measure a person's experience of presence and tendency to experience presence.
Michael Meehan, Brent Insko, Mary Whitton, Frederick P. Brooks Jr.. Physiological measures of presence in stressful virtual environments. ACM Transactions on Graphics, vol. 21, num. 3, pp. 645-652, 2002.
Describes a virtual reality experiment in which heart rate and skin conductivity were correlated with the experience of presence in the virtual environment.

Personality and Emotion

Colin G. DeYoung, Lena C. Quilty, Jordan B. Peterson. Between facets and domains: 10 aspects of the Big Five. Journal of Personality and Social Psychology, vol. 93, num. 5, pp. 880-896, 2007. American Psychological Association.
A survey of the Big Five (or OCEAN), a hierarchical, factor-based model of personality that has been highly studied and verified.
Albert Mehrabian. Analysis of the big-five personality factors in terms of the PAD temperament model. Australian Journal of Psychology, vol. 48, num. 2, pp. 86-92, 1996.
Connects the Big Five to the Pleasure Arousal Dominance (PAD) model of mood.
Carole Adam, Andreas Herzig, Dominique Longin. A logical formalization of the OCC theory of emotions. Synthese, vol. 168, num. 2, pp. 201-248, 2009. Springer.
Describes a logical formalization of the Ortony, Clore, and Collins (OCC) appraisal-based model of emotion.

Artificial Intelligence

General Resources

Stuart J. Russell, Peter Norvig. Artificial Intelligence: a modern approach. 2009. Pearson.
A widely used AI textbook covering a many topics.
Michael Bratman. Intention, plans, and practical reason. 1987. Harvard University Press.
The popular belief, desire, intention (BDI) software model outlines an architecture for intelligent agent behavior.
Mikhail Jacob, Sam Devlin, Katja Hofmann. ``It's unwieldy and it takes a lot of time''---Challenges and opportunities for creating agents in commercial games. In Proceedings of the 16th AAAI international conference on Artificial Intelligence and Interactive Digital Entertainment, pp. 88-94, 2020.
A qualitative survey of game developers who work on AI for agents in video games discussing the challenges they face.

Planning

Allen Newell, John C. Shaw, Herbert A. Simon. Report on a general problem-solving program. In Proceedings of the International Conference on Information Processing, pp. 256-264, 1959.
GPS (General Problem Solver) is often considered the first planner.
Richard E. Fikes, Nils J. Nilsson. STRIPS: a new approach to the application of theorem proving to problem solving. Artificial Intelligence, vol. 2, num. 3, pp. 189-208, 1972. Elsevier.
The STRIPS (Stanford Research Institute Problem Solver) representation and other STRIPS-like representations are commonly used to define planning problems.
Daniel S. Weld. An introduction to least commitment planning. AI magazine, vol. 15, num. 4, pp. 27-61, 1994.
A survey and introduction to partial order, causal link, and least commitment planning.
Daniel S. Weld. Recent advances in AI planning. AI Magazine, vol. 20, num. 2, p. 93, 1999.
A survey and introduction to plan graph planners and planning as satisfiability.
Malte Helmert. New complexity results for classical planning benchmarks. In Proceedings of the 16th International Conference on Automated Planning and Scheduling, pp. 52-62, 2006.
The computational complexity of the planning decision problem is PSPACE complete.

Partial Order Causal Link (POCL) Planning

Earl D. Sacerdoti. The nonlinear nature of plans. Stanford Research Institute, 1975.
First discussion of partially ordered plans.
David McAllester, David Rosenblitt. Systematic nonlinear planning. Massachusetts Institute of Technology Artificial Intelligence Laboratory, 1991.
SNLP (Systematic Non-Linear Planner) introduced causal links and was the first POCL planner.
J. Scott Penberthy, Daniel S. Weld. UCPOP: a sound, complete, partial order planner for ADL. In Proceedings of the 3rd International Conference on Principles of Knowledge Representation and Reasoning, vol. 92, pp. 103-114, 1992.
UCPOP is an iconic POCL planner.
XuanLong Nguyen, Subbarao Kambhampati. Reviving partial order planning. In Proceedings of the 17th International Joint Conference on Artificial Intelligence, pp. 459-464, 2001.
Describes several improvements to partial order planning, including the integration of modern state-space planning heuristics.

Forward-Chaining State Space Heuristic Search Planning

Blai Bonet, Héctor Geffner. Planning as heuristic search. Artificial Intelligence, vol. 129, num. 1, pp. 5-33, 2001. Elsevier.
HSP (Heuristic Search Planner) was the beginning of the state space heuristic search family of planners.
Jörg Hoffmann, Bernhard Nebel. The FF planning system: fast plan generation through heuristic search. Journal of Artificial Intelligence Research, vol. 14, pp. 253-302, 2001.
FF (Fast Forward) was a significant improvement over HSP.
Malte Helmert. The Fast Downward planning system.. Journal of Artificial Intelligence Research, vol. 26, pp. 191-246, 2006.
FD (Fast Downward) was a significant improvement over FF.
Malte Helmert. Translation. In Understanding Planning Tasks: Domain Complexity and Heuristic Decomposition, pp. 171-206, 2008. Springer.
A book chapter describing how Fast Downward translates traditional PDDL planning problems into multi-valued planning tasks.
Michael Katz, Jörg Hoffmann, Carmel Domshlak. Red-black relaxed plan heuristics. In Proceedings of the 23rd International Conference of Automated Planning and Scheduling, pp. 489-495, 2013.
An improvement to FF that only relaxes some variables to obtain more accurate relaxed plans.

Other Notable Planning Algorithms

Avrim L. Blum, Merrick L. Furst. Fast planning through planning graph analysis. Artificial Intelligence, vol. 90, num. 1, pp. 281-300, 1997. Elsevier.
Describes the GraphPlan algorithm.
Henry Kautz, David McAllester, Bart Selman. Encoding plans in propositional logic. KR, vol. 96, pp. 374-384, 1996.
Describes Blackbox and other efforts to translate planning problems into SAT problems.
Alfonso Gerevini, Alessandro Saetti, Ivan Serina. Planning through stochastic local search and temporal action graphs in LPG. Journal of Artificial Intelligence Research, vol. 20, pp. 239-290, 2003.
Describes the LPG (Local search in Plan Graphs) planning algorithm.
Hector Geffner, Nir Lipovetzky. Width and serialization of classical planning problems. In Proceedings of the 20th European Conference on Artificial Intelligence, pp. 540-545, 2012. IOS Press.
Describes the IW (Iterated Width) planner, a simple but effective blind search (i.e. no heuristic) algorithm.

Planning in AAA Video Games

Jeff Orkin. Agent architecture considerations for real-time planning in games. In Proceedings of the 1st AAAI international conference on Artificial Intelligence and Interactive Digital Entertainment, pp. 105-110, 2005.
F.E.A.R. uses real time planning to control its NPCs.
Alex J. Champandard, Tim Verweij, Remco Straatman. The AI for Killzone 2's multiplayer bots. In Proceedings of Game Developers Conference, 2009.
Killzone 2 uses HTN planning to control its NPCs.

Fast Planning in Academic Interactive Story Systems

Marc Cavazza, Fred Charles, Steven J. Mead. Character-based interactive storytelling. IEEE Intelligent Systems special issue on AI in Interactive Entertainment, vol. 17, num. 4, pp. 17-24, 2002.
Uses HSP to create an interactive narrative based on the TV show Friends.
David Pizzi, Marc Cavazza. Affective storytelling based on characters' feelings. In Proceedings of the AAAI Fall Symposium on Intelligent Narrative Technologies, pp. 111-118, 2007.
Uses HSP to create an interactive narrative based on Flaubert's novel Madame Bovary.
Julie Porteous, Marc Cavazza, Fred Charles. Applying planning to interactive storytelling: Narrative control using state constraints. ACM Transactions on Intelligent Systems and Technology, vol. 1, num. 2, pp. 1-21, 2010. ACM.
Uses fast planning with constraints to created an interactive narrative based on Shakespeare's The Merchant of Venice.
Stephen G. Ware, R. Michael Young, Christian Stith, Phillip Wright. Interactive narrative planning in The Best Laid Plans. In Proceedings of the 25th AAAI Conference on Artificial Intelligence, Virtual Agent Demonstrations, pp. 4313-4314, 2015.
The Best Laid Plans uses narrative planning to generate stories at run time that cause conflict.
Rachelyn Farrell, Stephen G. Ware. Fast and diverse narrative planning through novelty pruning. In Proceedings of the 12th AAAI international conference on Artificial Intelligence and Interactive Digital Entertainment, pp. 37-43, 2016.
Demonstrates that novelty pruning can improve the speed of several narrative planning algorithms.

Plan Recognition

Miquel Ramírez, Hector Geffner. Plan recognition as planning. In Proceedings of the 21st International Joint Conference on Artificial Intelligence, 2009.
Describes a framework for using a planner to recognize an agent's plan by filling in missing steps from a partial sequence of observations.
Rachelyn Farrell, Stephen G. Ware. Narrative planning for belief and intention recognition. In Proceedings of the 16th AAAI international conference on Artificial Intelligence and Interactive Digital Entertainment, pp. 52-58, 2020.
Uses the PRP framework for predicting the beliefs and intentions of agents based on their actions using narrative planning.

Computational Models of Narrative

Survey Papers

Pablo Gervás. Computational approaches to storytelling and creativity. AI Magazine, vol. 30, num. 3, p. 49, 2009.
Surveys early story generation systems up to 2007.
David L. Roberts, Charles L. Isbell. A survey and qualitative analysis of recent advances in drama management. International Transactions on Systems Science and Applications, Special Issue on Agent Based Systems for Human Learning, vol. 4, num. 2, pp. 61-75, 2008.
Surveys and evaluates various drama management approaches.
Maria Arinbjarnar, Heather Barber, Daniel Kudenko. A critical review of interactive drama systems. In Proceedings of the Society for the Study of Artificial Intelligence and the Simulation of Behaviour symposium on AI and Games, 2009.
Surveys many interactive narrative systems based on plot graphs.
Mark O. Riedl, Vadim Bulitko. Interactive narrative: an intelligent systems approach.. AI Magazine, vol. 34, num. 1, pp. 67-77, 2013.
Surveys and classifies interactive narrative systems up to 2012.
Erik T. Mueller. Computational models of narrative. Sprache und Datenverarbeitung, Special Issue on Formal and Computational Models of Narrative, vol. 37, num. 1-2, pp. 11-39, 2013.
Surveys systems for narrative understanding and generation, as well as issues of knowledge representation up to 2013.
R. Michael Young, Stephen G. Ware, Bradly A. Cassell, Justus Robertson. Plans and planning in narrative generation: a review of plan-based approaches to the generation of story, discourse and interactivity in narratives. Sprache und Datenverarbeitung, Special Issue on Formal and Computational Models of Narrative, vol. 37, num. 1-2, pp. 41-64, 2013.
Surveys plan-based models of narrative up to 2013.
Mark A. Finlayson. A survey of corpora in computational and cognitive narrative science. Sprache und Datenverarbeitung, Special Issue on Formal and Computational Models of Narrative, vol. 37, num. 1-2, pp. 113-141, 2013.
Surveys corpus-based approaches to narrative understanding.
Mark A. Finlayson, Steven R. Corman. The military interest in narrative. Sprache und Datenverarbeitung, Special Issue on Formal and Computational Models of Narrative, vol. 37, num. 1-2, pp. 173-191, 2013.
Describes why the military is interested in narrative research and several application areas.
Ben Kybartas, Rafael Bidarra. A survey on story generation techniques for authoring computational narratives. IEEE Transactions on Computational Intelligence and Artificial Intelligence in Games, vol. 9, num. 3, pp. 239-253, 2016.
A comprehensive survey of many different narrative generation systems.

Opinion Papers

Ian Horswill. Science considered harmful. In Proceedings of the 6th Intelligent Narrative Technologies workshop at the 9th AAAI international conference on Artificial Intelligence and Interactive Digital Entertainment, pp. 82-85, 2013.
Horswill argues that the emphasis on scientific rigor is harmful to the field of Intelligent Narrative Technologies and that it should adopt evaluation methods from the arts.
R. Michael Young. Science considered helpful. In Proceedings of the 11th International Conference on Interactive Digital Storytelling, pp. 21-35, 2018.
Young responds to Horswill, defending the value of scientific rigor and the scientific approach to INT.

Notable Systems

James R. Meehan. TALE-SPIN, an interactive program that writes stories. Proceedings of the 5th International Joint Conference on Artificial Intelligence, pp. 91-98, 1977.
TALE-SPIN is usually considered the first story generation system.
Natlie Dehn. Story generation after TALE-SPIN. In Proceedings of the 7th International Joint Conference on Artificial Intelligence, vol. 81, pp. 16-18, 1981.
AUTHOR focused on the author's goals rather than the character's goals.
Michael Lebowitz. Story-telling as planning and learning. Poetics, vol. 14, num. 6, pp. 483-502, 1985. Elsevier.
UNIVERSE combined plot fragments to generate serial stories.
Peter Weyhrauch. Guiding interactive drama. Ph.D. thesis at Carnegie Mellon University, 1997.
Moe is an early interactive drama architecture for guiding a user through a plot graph based on adversarial search and an aesthetic evaluation function.
R. Michael Young. An overview of the Mimesis architecture: integrating intelligent narrative control into an existing gaming environment. In Proceedings of the AAAI spring symposium on Artificial Intelligence and Interactive Entertainment, pp. 77-81, 2001.
Mimesis was one of the first 3D virtual environments to connect to a separate experience manager that uses a narrative planner to adapt a story in real time.
Rafael Pérez y Pérez, Mike Sharples. MEXICA: A computer model of a cognitive account of creative writing. Journal of Experimental & Theoretical Artificial Intelligence, vol. 13, num. 2, pp. 119-139, 2001. Taylor & Francis.
MEXICA models the cognitive process of human composition to create short stories.
Mariët Theune, Sander Faas, Anton Nijholt, Dirk Heylen. The Virtual Storyteller: story creation by intelligent agents. In Proceedings of the 1st international conference on Technologies for Interactive Digital Storytelling and Entertainment, pp. 204-215, 2003. Springer.
Virtual Storyteller focuses on strong autonomy agents but includes a director agent to look after the plot.
Michael Mateas, Andrew Stern. Structuring content in the Façade interactive drama architecture. In Proceedings of the 1st AAAI international conference on Artificial Intelligence and Interactive Digital Entertainment.
Façade is a fully-realized interactive drama using natural language parsing.
Mark J. Nelson, Michael Mateas, David L. Roberts, Charles L. Isbell. Declarative optimization-based drama management in interactive fiction. IEEE Computer Graphics and Applications, vol. 26, num. 3, pp. 32-41, 2006.
DODM (Declarative Optimization-based Drama Management) modifies the world to encourage players to take specific actions.
David Thue, Vadim Bulitko, Marcia Spetch, Eric Wasylishen. Interactive storytelling: a player modelling approach. In Proceedings of the 3rd AAAI international conference on Artificial Intelligence and Interactive Digital Entertainment, pp. 43-48, 2007.
PaSSAGE (Player-Specific Stories via Automatically Generated Events) categories players based on their actions and customizes the story accordingly.
Mark O. Riedl, Andrew Stern, Don Dini, 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, num. 2, pp. 23-42, 2008.
IN-TALE and ASD (Automated Story Director) analyse plans and how they can fail to create a personalized interactive experience.
Stacy C. Marsella, Jonathan Gratch. EMA: A process model of appraisal dynamics. Cognitive Systems Research, vol. 10, num. 1, pp. 70-90, 2009. Elsevier.
EMA is a system that reasons about an agent's emotional reactions to events and how emotions motivate changes in behavior.
Zach Tomaszewski. On the use of reincorporation in interactive drama. In Proceedings of the 4th Intelligent Narrative Technologies workshop at the 7th AAAI international conference on Artificial Intelligence and Interactive Digital Entertainment, pp. 84-91, 2011.
Marlinspike chooses a next event which best reincorporates past events, especially the player's, to create story unity.
Jonathan Teutenberg, Julie Porteous. Efficient intent-based narrative generation using multiple planning agents. In Proceedings of the 2013 international conference on Autonomous Agents and Multiagent Systems, pp. 603-610, 2013.
IMPRACTical is a fast intentional planner that first plans for each agent and then stitches agent plans together to form a story.
Joshua McCoy, Mike Treanor, Ben Samuel, Aaron A. Reed, Michael Mateas, Noah Wardrip-Fruin. Social story worlds with Comme il Faut. IEEE Transactions on Computational Intelligence and Artificial Intelligence in Games, vol. 6, num. 2, pp. 97-112, 2014.
Comme il Faut is the AI system which manages the social behaviors of characters in the game Prom Week.
Stephen G. Ware, R. Michael Young. Glaive: a state-space narrative planner supporting intentionality and conflict. In Proceedings of the 10th AAAI international conference on Artificial Intelligence and Interactive Digital Entertainment, pp. 80-86, 2014. (awarded Best Student Paper)
Glaive is a fast forward-chaining state space narrative planner supporting intentionality and conflict.
Michael Mateas, Peter Mawhorter, Noah Wardrip-Fruin. Intentionally generating choices in interactive narratives. In Proceedings of the Sixth International Conference on Computational Creativity, pp. 292-299, 2015.
Dunyazad automatically generates choose-your-own-adventure style stories using a simple but expressive theory of how people think about choices.
Richard Evans, Emily Short. Versu--a simulationist storytelling system. IEEE Transactions on Computational Intelligence and AI in Games, vol. 6, num. 2, pp. 113-130, 2013. IEEE.
Versu generates interactive stories where agents choose actions from social practices (scripted multi-agent plans) using utility functions and social simulation.
Yun-Gyung Cheong, R. Michael Young. Suspenser: a story generation system for suspense. IEEE Transactions on Computational Intelligence and Artificial Intelligence in Games, vol. 7, num. 1, pp. 39-52, 2015.
Suspenser uses plan-based models of narrative to generate stories which evoke a feeling of suspense by remmoving the number of successful foreseeable outcomes for the protagonist.
Boyang Li, Stephen Lee-Urban, Darren Scott Appling, Mark O. Riedl. Crowdsourcing narrative intelligence. Advances in Cognitive systems, vol. 2, num. 1, pp. 1-18, 2012.
Scheherazade learns plot graphs from a crowd-sourced corpus of simple stories about any topic.
Rogelio E. Cardona-Rivera, Boyang Li. PLOTSHOT: Generating discourse-constrained stories around photos. In Proceedings of the 12th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, pp. 2-8, 2016.
PLOTSHOT uses the Glaive narrative planner to create stories from a sequence of photos.
Brent Harrison, Mark O. Riedl. Learning from stories: using crowdsourced narratives to train virtual agents. In Proceedings of the 12th AAAI international conference on Artificial Intelligence and Interactive Digital Entertainment, pp. 183-189, 2016.
Quixote uses reinforcement learning to train agents to behave like characters from a crowd-sourced corpus of simple stories.

Plan-Based Models of Narrative

See also: Plans and planning in narrative generation: a review of plan-based approaches to the generation of story, discourse and interactivity in narratives.
R. Michael Young. Notes on the use of plan structures in the creation of interactive plot. In Proceedings of the AAAI Fall Symposium on Narrative Intelligence, pp. 164-167, 1999.
Early discussion on the use of partial order causal link plans to represent and generate stories.
Mark O. Riedl, R. Michael Young. Narrative planning: balancing plot and character. Journal of Artificial Intelligence Research, vol. 39, num. 1, pp. 217-268, 2010.
Describes intentional planning and the IPOCL algorithm, which attempts to balance both the author's goal and the goals of individual characters.
Patrik Haslum. Narrative planning: compilations to classical planning. Journal of Artificial Intelligence Research, vol. 44, pp. 383-395, 2012.
Shows that Riedl and Young\s IPOCL model of intentionality can be compiled to classical planning problems which may be solved faster by modern planners.
Arnav Jhala, R. Michael Young. Cinematic visual discourse: representation, generation, and evaluation. IEEE Transactions on Computational Intelligence and Artificial Intelligence in Games, vol. 2, num. 2, pp. 69-81, 2010.
Describes Darshak, a planning system for composing and visualizing narratives in cinema.
See also: Indexter: a computational model of the Event-Indexing Situation Model for characterizing narratives.
Byung-Chull Bae, R. Michael Young. A computational model of narrative generation for surprise arousal. IEEE Transactions on Computational Intelligence and Artificial Intelligence in Games, vol. 6, num. 2, pp. 131-143, 2014.
Describes Prevoyant, a planning system that generates stories which elicit surprise using flashbacks and foreshadowing.
Stephen G. Ware, R. Michael Young, Brent Harrison, David L. Roberts. A computational model of narrative conflict at the fabula level. IEEE Transactions on Computational Intelligence and Artificial Intelligence in Games, vol. 6, num. 3, pp. 271-288, 2014.
Describes CPOCL, a model of conflict based on threatened causal links.
Alireza Shirvani, Rachelyn Farrell, Stephen G. Ware. Combining intentionality and belief: revisiting believable character plans. In Proceedings of the 14th AAAI international conference on Artificial Intelligence and Interactive Digital Entertainment, pp. 222-228, 2018.
Describes a combined plan-based model of belief and intention and how they influence one another.
Alireza Shirvani, Stephen G. Ware. A formalization of emotional planning for strong-story systems. In Proceedings of the 16th AAAI international conference on Artificial Intelligence and Interactive Digital Entertainment, pp. 116-122, 2020.
Descibres how changes in agent utility can be used to simulate emotions and motivation actions based on those emotions.

Intelligent Tutoring and Training

Survey Papers

Kurt VanLehn. The behavior of tutoring systems. International Journal of Artificial Intelligence in Education, vol. 16, num. 3, pp. 227-265, 2006.
A seminal survey of intelligent tutoring systems research by a leading researcher in the field.
Amy L. Alexander, Tad Brunyé, Jason Sidman, Shawn A. Weil. From gaming to training: A review of studies on fidelity, immersion, presence, and buy-in and their effects on transfer in pc-based simulations and games. In DARWARS Training Impact Group, 2005.
Surveys many factors that are important to virtual training and which may lead to improved transfer of knowledge from the virtual world to the real world.
Wenting Ma, Olusola O. Adesope, John C. Nesbit, Qing Liu. Intelligent tutoring systems and learning outcomes: a meta-analysis. Journal of Educational Psychology, vol. 106, num. 4, pp. 901–-918, 2014.
A meta-survey of 107 intelligent tutoring systems involving 14,321 human subjects demonstrating that they improve learning and retention.
James A. Kulik, J. D. Fletcher. Effectiveness of intelligent tutoring systems: a meta-analytic review. Review of Educational Research, vol. 86, num. 1, pp. 42-78, 2016.
A meta-survey of 50 intelligent tutoring systems demonstrating that they significantly improve learning.

Transfer, Presence, Fidelity, Immersion, etc.

Bob G. Witmer, Michael J. Singer. Measuring presence in virtual environments: a presence questionnaire. Presence: Teleoperators and Virtual Environments, vol. 7, num. 3, pp. 225-240, 1998. MIT Press.
Describes a questionnaire for measuring the subjective experience of presence (closely related to agency) in virtual task environments.
Jonathan A. Stevens, J. Peter Kincaid. The relationship between presence and performance in virtual simulation training. Open Journal of Modelling and Simulation, vol. 3, pp. 41-48, 2015.
Finds some evidence that improved persence leads to improved performance, which may in turn lead to improved transfer. Includes a good related work section on the relationship between presence, performance, fidelity, and transfer.

Intelligent Tutoring Systems in Education

James M. Thomas, R. Michael Young. Annie: Automated generation of adaptive learner guidance for fun serious games. IEEE Transactions on Learning Technologies, vol. 3, num. 4, pp. 329-343, 2010.
An interactive narrative serious game designed to teach players about cybersecurity that uses planning to automatically adapt the narrative based on what the user does and does not know.
Jonathan P. Rowe, Lucy R. Shores, Bradford W. Mott, James C. Lester. Integrating learning, problem solving, and engagement in narrative-centered learning environments. International Journal of Artificial Intelligence in Education, vol. 21, num. 1-2, pp. 115-133, 2011.
Crystal Island is a game-based learning environment that teaches eighth-grade microbiology. The study described in this paper demonstrated a link between student engagement with the game and learning outcomes.

Military Training Simulations

Richard H. Stottler, Michael Vinkavich. Tactical Action Officer Intelligent Tutoring System (TAO ITS). Defense Technical Information Center, 2006.
Describes the Tactical Action Officer Intelligent Tutoring System, which allowed the Navy to improve the tactical training of new officers using virtual training scenarios.
Alexander Zook, Stephen Lee-Urban, Mark O. Riedl, Heather K. Holden, Robert A. Sottilare, Keith W. Brawner. Automated scenario generation: toward tailored and optimized military training in virtual environments. In Proceedings of the 7th international conference on the Foundations of Digital Games, pp. 164-171, 2012.
Many diverse training scenarios are generated to suit the needs of the individual trainee using a genetic algorithm.

Other Applications

Kenneth Hullett, Michael Mateas. Scenario generation for emergency rescue training games. In Proceedings of the 4th international conference on Foundations of Digital Games, pp. 99-106, 2009.
An HTN planner is used to generate training scenarios for emergency rescue workers that need to focus on specific skills.