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Schedule: CompSci 765 / Semester 1

Interactive Cognitive Systems

Note this is the 2015 version of the website; 2016 update coming shortly.

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Week 1

2 March. Introduction to interactive cognitive systems

• Lecture notes

3 March. Motivating examples

• Laird, J. E. (2002). Research in human-level AI using computer games. Communications of the ACM, 45, 32-35.
• Swartout, W. R., Gratch, J., Hill, R. W., Hovy, E., Marsella, S., Rickel, J., & Traum, D. (2006). Toward virtual humans. AI Magazine, 27, 96-108.

4 March. Frameworks for intelligent systems

• Newell, A., & Simon, H. A. (1976). Computer science as empirical enquiry: Symbols and search. Communications of the ACM, 19, 113-126.
• Slade, S. (1991). Case-based reasoning: A research paradigm. AI Magazine, 12, 42-55. [optional]
• Lecture notes

Week 2

9 March. Technology: Cognitive control / Production systems

• Young, R. M. (2001). Production systems in cognitive psychology. In N. J. Smelser & P. B. Baltes (eds.), International Encyclopedia of the Social and Behavioral Sciences. Pergamon.
• Jones, G., & Ritter, F. E. (2003). Production systems and rule-based inference. Encyclopedia of Cognitive Science. London: Macmillan.
• Lecture notes

10 March. Technology: Problem Solving and Planning

• Hendler, J., Tate, A., & Drummond, M. (1990). AI planning: Systems and techniques. AI Magazine, 11, 61-77.
• Nau, D., Cao, Y., Lotem, A., & Munoz-Avila, H. (1999). SHOP: A simple hierarchical ordered planner. Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence (pp. 968-973).
• Lecture notes

11 March. Application: Synthetic opponents / Game-playing systems

• Wray, R. E., Laird, J. E., Nuxoll, A., Stokes, D., Kerfoot, A. (2005). Synthetic adversaries for urban combat training. AI Magazine, 26, 82-92.
• Best, B. J., Lebiere, C., & Scarpinatto, K. C. (2002). Modeling synthetic opponents in MOUT training simulations using the ACT-R cognitive architecture. Proceedings of the Eleventh Conference on Computer-Generated Forces and Behavior Representation (pp. 505-516). [optional]
• Smith, S. J., Nau, D., & Throop, T. (1998). Computer Bridge: A big win for AI planning. AI Magazine, 19, 93-106. [optional]

Week 3

16 March. Application: Human-Robot Interaction

• Talamadupula, K., Briggs, G., Chakraborti, T., Scheutz, M., & Kambhampati, S. (2014) Coordination in human-robot teams using mental modeling and plan recognition. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (pp. 2957-2962). Chicago: IEEE Press. [Video]
• Trivedi, N., Langley, P., Schermerhorn, P., & Scheutz, M. (2011). Communicating, interpreting, and executing high-level instructions for human-robot interaction. Proceedings of the AAAI Fall Symposium on Advances in Cognitive Systems. Arlington, VA: AAAI Press. [optional]

17 March. Application: Interactive entertainment

• Mateas, M., & Stern, A. (2006). Structuring content in the Facade interactive drama architecture. Proceedings of the Conference on Artificial Intelligence and Interactive Digital Entertainment. Los Angeles: AAAI Press.
• The Facade system.

18 March. Application: System-Level Research Challenges

• Langley, P. (2014). Four research challenges for cognitive systems. Advances in Cognitive Systems, 3, 3-11.
• Hatsuke Miku performing on David Letterman.
• Evans, R., & Short, E. (2014). Versu — A simulationist storytelling system. IEEE Transactions on Computational Intelligence and AI in Games, 6, 113-130. [optional]
• Lecture notes

Week 4

23 March. Methods: Domain and task analysis 1

• Slides here [no reading for student presentation]

24 March. Methods: Domain and task analysis 2

• Continue from yesterday's slides [no reading for student presentation]
• Guidelines for major assignment included with slides

25 March. Methods: Modelling interaction

• Drury, J., Scholtz, J., & Kieras, D. (2007) Adapting GOMS to model human-robot interaction. Proceedings of the ACM/IEEE International Conference on Human-Robot Interaction. New York: ACM. [log onto ACM digital library and search for title]
• Mark Claypool, Paolo Piselli, and Jim Doyle (2009) Relating Cognitive Models of Computer Games to User Evaluations of Entertainment In Proceedings of the 4th ACM International Conference on the Foundations of Digital Games (FDG), Florida, USA, April 26-30, 2009.

Week 5

30 March. Technology: Multi-agent systems

• Tambe, M. (1997). Agent architectures for flexible, practical teamwork. Proceedings of the Fourteenth National Conference on Artificial Intelligence (pp. 22-28). Providence, RI: AAAI Press.
• M. Tambe, E. Bowring, J. P. Pearce, P. Varakanthan, P. Scerri, & D. V. Pydnath (2008). Electric Elves: What went wrong and why. AI Magazine, 29, 23-31. [optional]
• Lecture notes

31 March. Application: Planning aids / Mixed-initiative planning

• Ferguson, G., & Allen, J. (2007). Mixed-initiative systems for collaborative problem-solving. AI Magazine, 28, 23-32.
• Bresina, J. L., & Morris, P. H. (2007). Mixed-initiative planning in space mission operations. AI Magazine, 28, 75-88.

1 April. Technology: Consideration in mixed-initiative interaction

• Horvitz, E. Principles of mixed-initiative user interfaces. Proceeding of the SIGCHI Conference on Human Factors in Computing Systems (pp. 159-166). New York: ACM.

Mid-Semester Break

Week 6

20 April. Usability: Understanding Experience in Interactive Systems

• Forlizzi, J. (2004) Understanding experience in interactive systems. Proceedings of the Fifth Conference on Designing Interactive Systems: Processes, Practices, Methods, and Techniques (pp. 261-268). New York: ACM.
• Lecture Notes

21 April. Application: Beating Common Sense into Interactive Applications

• Lieberman H., Liu H., Singh P., Barry B.(2004). Beating common sense into interactive applications. AI Magazine, 25, 63-76.
• Push Singh, Thomas Lin, Erik T. Mueller, Grace Lim, Travell Perkins, Wan Li Zhu. (2002). Open Mind Common Sense: Knowledge Acquisition from the General Public. On the Move to Meaningful Internet Systems 2002: CoopIS, DOA, and ODBASE Lecture Notes in Computer Science Volume 2519 pp 1223-1237 [optional]
• Review Notes

22 April. Mid-term test: About 40 minutes, in class

Week 7

27 April. Anzac Holiday (No Lecture)

28 April. Technology: Plan recognition / understanding

• Carberry, S. (2001). Techiques for plan recognition. User Modeling and User-Adapted Interaction, 11, 31-48.
• Raskutti, B., & Zukerman, I. (1991). Generation and selection of likely interpretations during plan recognition in task-oriented consultation systems. User Modeling and User-Adapted Interaction, 1, 323-353. [optional]
• Bauer, M., & Paul, G. (1993). Logic-based plan recognition for intelligent help systems. DFKI Research Report 93-43, German Research Center for Artificial Intelligence, Saarbrucken, Germany. [optional]
• Lecture notes

29 April. Technology: Social understanding and planning

• Meadows, B., Langley, P., & Emery, M. (2014). An abductive approach to understanding social interactions. Advances in Cognitive Systems, 3, 87-106
• Pearce, C., Meadows, B., Langley, P., & Barley, M. (2014). Social planning: Achieving goals by altering others' mental states. Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence. Quebec City, Quebec: AAAI Press. [optional]
• Brenner, M. (2010). Creating dynamic story plots with continual multiagent planning. Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence (pp. 1517-1522). AAAI Press. [optional]
• Lecture notes

Week 8

4 May. Technology: Introduction to dialogue processing

• Allen, J., Byron, D., Dzikovska, M., Ferguson, G., Galescu, L., & Stent, A. (2001). Towards conversational human-computer interaction. AI Magazine, 22, 27-38.
• Wikipedia entry for ELIZA.
• Allen, J. F., Miller, B. W., Ringger, E. K., & Sikorski, T. (1996). A robust system for natural spoken dialogue. Proceedings of the 1996 Annual Meeting of the Association for Computational Linguistics (pp. 62-70). [optional]
• Lecture notes

5 May. Application: Conversational recommendation systems

• Thompson, C. A., Goker, M., & Langley, P. (2004). A personalized system for conversational recommendations. Journal of Artificial Intelligence Research, 21, 393-428.
• Aha, D. W., McSherry, D., & Yang, Q. (2006). Advances in conversational case-based reasoning. Knowledge Engineering Review, 20, 247-254. [optional]

6 May. Application: Conversational mentors

• Rich, C., Sidner, C. L., & Lesh, N. (2001). COLLAGEN: Applying collaborative discourse theory to human-computer interaction. AI Magazine, 22, 15-26
• Gabaldon, A., Langley, P., & Meadows, B. (2014). Integrating meta-level and domain-level knowledge for task-oriented dialogue. Advances in Cognitive Systems, 3, 201-219. [optional]

Week 9

11 May. Advanced topic: Emotion and cognition

• Lin, J., Spraragen, M., & Zyda, M. (2012). Computational models of emotion and cognition. Advances in Cognitive Systems, 2, 59-76.
• Gratch, J. (2000). Emile: Marshalling passions in training and education. Proceedings of the Fourth International Conference on Autonomous Agents, Barcelona, Spain. [optional]
• Marinier, R. P., Laird, J. E., & Lewis, R. L. (2009). A computational unification of cognitive behavior and emotion. Cognitive Systems Research, 10, 48–69. [optional]
• Lecture notes

12 May. Advanced topic: Personality and cognition

• Rizzo, P., Veloso, M., Miceli, M., & Cesta, A. (1997). Personality-driven social behaviors in believable agents. Proceedings of the AAAI Fall Symposium on Socially Intelligent Agents. Cambridge, MA: AAAI Press.
• Coman, A., & Munoz-Avila, H. (2012). Plan-based character diversity. Proceedings of the Eighth Artificial Intelligence and Interactive Digital Entertainment Conference (pp. 118-123). [optional]
• Rousseau, D., & Hayes-Roth, B. (1996). Personality in synthetic agents (Report No. KSL 96-21). Knowledge Systems Laboratory, Department of Computer Science, Stanford University, Stanford, CA. [optional]
• Lecture notes

13 May. Advanced topic: Moral cognition

• Mikhail, J. (2007). Universal moral grammar: Theory, evidence and the future. Trends in Cognitive Science, 11, 143-152.
• Arkin, A. C., & Ulam, P. (2009). An ethical adaptor: behavioral modification derived from moral emotions. Proceedings of the Eighth IEEE International Conference on Computational Intelligence in Robotics and Automation (pp. 381-387). IEEE Press. [optional]
• Dehghani, M., Tomai, E., Forbus, K. & Klenk, M. (2008). An integrated reasoning approach to moral decision-making. Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence. Chicago: AAAI Press. [optional]
• Meadows, B., Heald, R., & Langley, P. (2014). Representations and mechanisms for moral understanding. Unpublished manuscript, Department of Computer Science, University of Auckland, Auckland, NZ. [optional]

Week 10

18 May. Application: Health consumer support

• Gustafson, D., Hawkins, R., McTavish, F., Pingree, S., Chen, W., Volrathongchai, K., Stengle, W., Stewart, J., & Serlin R. (2008). Internet-based interactive support for cancer patients: Are integrated systems better? Journal of Communication, 58, 238-257.
• Guest Lecture notes from Prof Jim Warren

19 May. Technology: Ubiquitous monitoring

• Hong, X., Nugent, C., Mulvenna, M., McClean, S., Scotney, B., & Delvin, S. (2009). Evidential fusion of sensor data for activity recognition in smart homes. Pervasive and Mobile Computing, 5, 236-252.
• Boger, J., Hoey, J., Poupart, P., Boutilier, C., Fernie, G., & Mihailidis, A. (2006). A planning system based on Markov decision processes to guide people with dementia through activities of daily living. IEEE Transactions on Information Technology in Biomedicine, 10(2), 323-333. [optional]
• Lecture notes

20 May. Application: Crisis Counseling

• K Dinakar, J Chen, H Lieberman, R Picard, R Filbin Mixed-Initiative Real-Time Topic Modeling & Visualization for Crisis Counseling Proceedings of the 20th International Conference on Intelligent User Interfaces (pp. 417--426)

Week 11

25 May. Application: Tutoring systems 1

• Brusilovskiy, P. L. (1994). The construction and application of student models in intelligent tutoring systems. Journal of Computer and Systems Sciences International, 32, 70-89.
• Graesser, A. C., VanLehn, K., Rosé,C. P., Jordan, P.W., & Harter, D. (2001). Intelligent tutoring systems with conversational dialogue. AI MAgazine, Winter, 39-51. [optional]
• Lecture notes

26 May. Application: Tutoring systems 2 & Web browsers

• Anderson, J., & Reisner, B. (1985). The LISP Tutor. BYTE, April, 159-175.
• Faaborg E., Lieberman H.(2006). A goal-oriented Web browser Proc. of the SIGCHI Conf. on Human Factors in Computing Systems (CHI ’06) (pp. 751--760). Washington, D.C.: American Medical Informatics Asociation.

27 May. Brainstorm: MOOC design, delivery and assessment

• Daradoumis, T., Bassi, R., Xhafa, F., & Caballe, S. (2013). A review on massive e-learning (MOOC) design, delivery and assessment. Proceedings of the Eighth International Conference on P2P, Parallel, Grid, Cloud and Internet Computing. IEEE Computer Society.

Week 12

1 June. Queen's Birthday (No lecture)

2 June. Student presentations based on major assignments

3 June. Course review Revision Notes

Lectures end.

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