Reading List

Below is a list of important publications that all NIL members should read.

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.

  • 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.

  • Janet Horowitz Murray. Hamlet on the holodeck: the future of narrative in cyberspace. 1997. Simon and Schuster.

    A vision for the future of storytelling.

Possible Worlds

Interactive Narrative

Agency

Cognitive Science

General Information

Planning and Causality in Narrative

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.

  • 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.

  • Christopher Kives, Stephen G. Ware, Lewis J. Baker. Evaluating the pairwise event salience hypothesis in Indexter. In Proceedings of the 11th AAAI International Conference on Artificial Intelligence and Interactive Digital Entertainment, pp. 30-36, 2015.

    A complicated human subjects trail which validated the use of EISM indices in plan-based stories.

  • Rachelyn Farrell, Stephen G. Ware. Predicting user choices in interactive narratives using Indexter's pairwise event salience hypothesis. In Proceedings of the 9th International Conference on Interactive Digital Storytelling, pp. 147-155, 2016.

    Demonstrates that EISM indices can be used not only to reason about past events but also predict future choices.

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.

Presence and Engagement

AI Planning

General Information

  • 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

Other Notable Planning Algorithms

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 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.

Computational Models of Narrative

Survey Papers

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.

  • 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.

  • 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.

  • 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.

Plan-Based Models

Intelligent Tutoring and Training

Survey Papers

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

Military Training Simulations

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.