Site Network: Cognitive Systems | SFB/TR 8 Spatial Cognition | Fachbereich 03 | Universität Bremen

Cognitive Modeling - WS 2011/12

Course 03-MB-711.02

Holger Schultheis, Thomas Barkowsky, Christian Freksa

Winter 2011/12
Mondays 8:45 - 10:15h & 10:30 - 12:00h Cartesium Rotunde
4 SWS (ECTS: 6)

Syllabus

A Introduction

1) 31 Oct 11:

B Cognitive Architectures & ACT-R

2) 07 Nov 11:

3) 14 Nov 11:
  • Practical introduction to ACT-R: ACT-R Tutorials I and II
  • Practical introduction to ACT-R: ACT-R Tutorials III and IV (old)
  • Presentation and discussion of solutions to Exercise 1
  • Homework: Exercise 2

C Philosophical Considerations

4) 21 Nov 11:

D Connectionism

5) 28 Nov 11:

6) 05 Dec 11:

E Parameter Estimation

7) 12 Dec 11:

F Dynamic Systems

8) 19 Dec 11:

9) 09 Jan 12:

G Model Evaluation

10) 16 Jan 12:

11) 23 Jan 12:

12) 30 Jan 12:

H Advanced Topics & Applications

13) 06 Feb 12:

14) 13 Feb 12:

Reading Material

All reading material will be made available as pdf files once the course starts.

  • Anderson, J. R. et al. (2004). An integrated theory of the mind. Psychological Review, 111.
  • Best, B.J., Furjanic, C., Gerhart, N., Fincham, J. M., Gluck, K. A., Gunzelmann, G., Krusmark, M., (2009). Adaptive Mesh Refinement for Efficient Exploration of Cognitive Architectures and Cognitive Models. In Proceedings of the 9th International Conference of Cognitive Modeling, Manchester, United Kingdom.
  • Busemeyer, J. R. (2003). Dynamic Systems. In L. Nadel (Ed.), Encyclopedia of cognitive science. London, UK: Macmillan Publishers.
  • Copeland, J. (1993). Artificial intelligence: A philosophical introduction. , MA: Blackwell Publishing.
  • Corbett, A.T., Anderson, J. R., & O'Brien, A.T. (1995). Student modeling in the ACT Programming Tutor. In P. Nichols, S. Chipman and B. Brennan (eds.) Cognitively Diagnostic Assessment. Hillsdale, NJ: Erlbaum.
  • Davis, R., & King, J. J. (1985). The origin of rule-based systems in AI. In B. G. Buchanan and E. H. Shortliffe (Eds.), Rule-Based Expert Systems. Reading, MA: Addison-Wesley.
  • Efron, B., & Tibshirani, R. J. (1993). An introduction to the Bootstrap. New York: Chapman & Hall.
  • Efron, B. & Tibshirani, R. J. (1997). Improvements on Cross-Validation: The .632+ Bootstrap method. Journal of the American Statistical Association, 92.
  • Grant, D. A. (1962). Testing the null hypothesis and the strategy and tactics of investigating theoretical models. Psychological Review, 69.
  • Jones, R. M., Crossman, J. A., Lebiere, C., & Best, B. J. (2006). An abstract language for cognitive modeling. In Proceedings of the Seventh International Conference on Cognitive Modeling. Trieste, Italy.
  • Lehman, J. F., Laird, J., & Rosenbloom, P. (1996). A gentle introduction to Soar, an architecture for human cognition.In S. Sternberg & D. Scarborough (Eds.), Invitation to cognitive science, Volume 4. Cambridge, MA: MIT Press.
  • Madras, N. N. (2002). Lectures on Monte Carlo Methods. Providence, Rhode Island: American Mathematical Society.
  • McCloskey, M. (1991). Networks and theories: The place of connectionism in cognitive science. Psychological Science, 2.
  • Pitt, M. A., Myung, J. (2002). When a good fit can be bad. Trends in Cognitive Sciences, 6(10).
  • Press, W. H.,  Teukolsky, S. A., Vetterling, W. T., and Flannery, B. P. (2007). Numerical Recipes: The Art of Scientific Computing. Cambridge: Cambridge University Press.
  • Newell, A. (1973). You can't play 20 questions with nature and win: Projective comments on the papers of this symposium. In W. G. Chase (Ed.), Visual Information Processing, New York: Academic Press.
  • Roberts, S., & Pashler, H. (2000). How persuasive is a good fit? A comment on theory testing. Psychological Review, 107.
  • Russell, S., & Norvig, P. (2003). Artificial intelligence: A modern approach. Upper Saddle River, NJ: Pearson Education.
  • Schöner, G. (2008). Dynamical systems approaches to cognition. In R. Sun (Ed.), The Cambridge Handbook of Computational Psychology. New York, NY: Cambridge University Press.
  • Snyman, J. A. (2005). Practical Mathematical Optimization. Berlin: Springer.
  • St. Amant, R., Horton, T. E., & Ritter, F. E. (2007). Model-based evaluation of expert cell phone menu interaction. ACM Transactions on Computer-Human Interaction, 14(1).
  • Sun, R. (2008). Introduction to computational cognitive modeling. In R. Sun (Ed.), The Cambridge Handbook of Computational Psychology. New York, NY: Cambridge University Press.
  • Thomas, M. S. C., & McClelland, J. L. (2008). Connectionist models of Cognition. In R. Sun (Ed.), The Cambridge Handbook of Computational Psychology. New York, NY: Cambridge University Press.
  • Usher, M., & McClelland, J. L. (2001). The time course of perceptual choice: The leaky, competing accumulator model. Psychological Review, 108.
  • van Gelder, T. (1998). The dynamical hypothesis in cognitive science. Behavioral and Brain Sciences, 21.
  • Shiffrin, R. M., Lee, M. D., Kim, W., & Wagenmakers, E.-J. (2008). A survey of model evaluation approaches with a tutorial on hierarchical Bayesian methods. Cognitive Science, 32.

 

Assignments / Credits

Here are a few notes on grading and other formal aspects of the course. To receive credits for the course you will need to actively and continually participate throughout the semester; this includes:
  • to read all papers,
  • to prepare 2 questions regarding each topic (based on the reading material for this topic),
  • to present at least one topic,
  • to solve 7 exercises, and
  • to present and discuss your solutions to the exercises.
Questions for each topic have to be submitted by email to cosy-exercises@informatik.uni-bremen.de by Sundays preceding the day when the corresponding topic is presented and discussed. Questions will be graded according to quality and will account for 20% of your overall grade. For example, questions only asking for key terms (explained) in the reading material of the topic (e.g., "What is Spatial Cognition?") will receive no credit. Questions should rather address conceptual issues arising from the text such as, for instance, regarding seeming contradictions or feasibility issues.
 
Presentations should be well-prepared, well-informed, and above all serve to help your classmates learn about and understand the facts and issues connected with your topic and it should enable them to enter into a qualified discussion about it. Ideally, plan on a 30 - 45 min duration for your presentation and a subsequent in-depth discussions (which you will also moderate). Presentations will be graded and will account for 35% of your overall grade.
 
You will also need to complete seven exercises in small groups, ideally with 2-3 members per group. A successful completion of an exercise should include a detailed written documentation (to be handed in before the deadline; see below for submission dates) and a presentation of the solution in class. Each group member should present at least once. In the seven exercises, you will need to reach an average score of at least 50%. At the end of the winter term, there will be a technical discussion of 20-30 minutes with every group to check whether the marks achieved by a group in the exercises are equally applicable to all individual group members, and to decide on individual marks. Your individual exercise mark will account for 45% of your final grade in the course.

Return dates for your completed exercises:

No. 1: 13.11.  
No. 2:  27.11.
No. 3:  11.12.
No. 4:  08.01.
No. 5:  22.01.
No. 6:  05.02.
No. 7:  12.02.
 
Please email your solutions in time to cosy-exercises@informatik.uni-bremen.de
 

Collaboration vs. Cheating

We much encourage collaboration and collaborative work will be especially required when completing your exercises. However, collaboration is to be sharply distinguished from cheating. No forms of cheating (including plagiarism) will be tolerated! If you do, rest assured that we will find out about it. Should you be caught cheating, this will result in your automatic failure of the course.

 

Exam

Technical discussions ("Fachgespräche") in Cognitive Modeling are scheduled for Wednesday, 29 Feb 12 (and Friday, 23 Mar 12, for repeaters). To participate in a technical discussion, please register by 14 Feb 12 (or by 11 Mar 12, for repeaters) by sending an email to cosy@informatik.uni-bremen.de. The email should list the names of all participants of the group (one email per group is enough). Please note that the successful completion of the exercises is a precondition for registering for a technical discussion.