Detailed Course Descriptions

Course Description

Cognitive Modelling:
Building Generative Theories

Gerhard Strube

University of Freiburg, Germany

strube@cognition.iig.uni-freiburg.de

Cognitive modelling is the central methodology of cognitive science, combining methods of both formal and empirical analysis with techniques for computer simulation. Theories based on cognitive models are generative theories because they can produce the very phenomena that we are interested in explaining.

This course will cover an overview spanning many different approaches. Some examples will be presented and discussed in depth. You will also gain some hands-on experience with cognitive modelling.

1. Different approaches to modelling: the case of word association and semantic memory

Word association: measuring the stream of associations
Mathematical equations as descriptive models: Bousfield & Sedgewick (1944)
Implicit process assumptions in descriptive models
Critique of Bousfield & Sedgewick
Alternatives: statistical models and their implicit assumptions

Required Readings

Strube, G. (2001). Generative theories in cognitive psychology. Theory & Psychology, 10, 117-125.

Optional Readings

Woodworth, R. S., & Schlosberg, H. (1954). Experimental psychology (rev. ed., ch. 3, pp. 43-71). New York: Holt, Rinehart & Winston.

2. Word association continued: the structure of memory and the retrieval process

Analyzing the single case: semantic clusters in associative production
Psycholinguistic theories of word association
Semantic similarity by ratings and associations: dissociating structure and process
Basic associative memory as a distributed storage device: concepts as feature vectors
Strategic control of retrieval: selective perspectives
The hybrid model in action: an evaluation

Required Readings

Kohonen, T., Oja, E., & Lehtiö, P. (1989). Storage and processing of information in distributed associative memory systems. In G. E. Hinton & J. A. Anderson (Eds.), Parallel models of associative memory (2^nd ed., pp. 129-167). Hillsdale, NJ: Erlbaum.

Optional Readings

Strube, G. (1991). Dynamic perspective in distributed representations. Zeitschrift für Psychologie, 199, 289-298.

3. Modelling in theoretical perspective

Consciousness: mental models of the world and oneself in it
Cognitive modelling as the construction of second-order models
Modelling as theory construction: advantages and pitfalls
Cognitive architectures, and recent developments in ACT-R
A case study: human action control and the goal stack
Pros and cons of cognitive architectures and theory-free frameworks

Required Readings

Strube, G. (2001). Cognitive modeling: research logic in cognitive science. In N. J. Smelser & P. B. Baltes (Eds.), International encyclopedia of the social and behavioral sciences (pp. 2124-2128). Oxford: Elsevier Science.

Optional Readings

Simon, H. A., & Wallach, D. (1999). Cognitive modeling in perspective. Kognitionswissenschaft, 8, 1-4.

Anderson, J. R., Bothell, D., Byrne M. D. & Lebiere, C. (submitted). An Integrated Theory of the Mind. Psychological Review. (available from http://act-r.psy.cmu.edu/publications/)

4. A second in-depth example: Mental models in spatial reasoning

3-tts problems in spatial reasoning: an ecological example
Two theories of human reasoning: proof theory vs. mental model theory (MMT)
Spatial reasoning with interval relations: formal analyses
Empirical findings: preferred initial models
Modelling model construction: local processes operating on an analogue representation
Evaluating the model

Required Readings

Schlieder, C. (1999). The construction of preferred mental models in reasoning with interval relations. In G. Rickheit & C. Habel (Eds.), Mental models in discourse processing and reasoning (Advances in Psychology, vol. 128, pp. 333-357).

Optional Readings

Knauff, M., Rauh, R., Schlieder, C., & Strube, G. (1998). Mental models in spatial reasoning. In C. Freksa, C. Habel & K. F. Wender (Eds.), Spatial cognition (Lecture Notes in Artificial Intelligence, vol. 1404, pp. 267-291.

Berendt, B. (1996). Explaining preferred mental models in Allen inferences with a metrical model of imagery. Proceedings of the 18^th Annual Conference of the Cognitive Science Society (pp. 489-494). Mahwah, NJ: Erlbaum.

5. Modelling in applied contexts: Cognitive task analysis, GOMS, etc.

Grain-size of cognitive modelling, and the importance of tasks
Task analysis: hierarchical task decomposition, dependency analysis, etc.
The GOMS keystroke model and Newell’s engineering model of human cognition
CP/GOMS and the case of Project Ernestine
Beyond GOMS: human error, and learning
Coarse-grained modelling communication of knowledge in teams of heterogeneous experts

Required Readings

Kieras, D. (1997). A Guide to GOMS model usability evaluation using NGOMSL. In M. G. Helander, T. K. Landauer & P. V. Prabhu (Eds.), Handbook of human-computer interaction (2^nd ed., pp. 733-766). Amsterdam: North Holland (Elsevier).

Optional Readings

Gray, W. D., John, B. E., & Atwood, M. E. (1993). Project Ernestine: a validation of GOMS for prediction and explanation of real-world task performance. Human-Computer Interaction, 8, 237-309.