Theoretical Modeling for Cognitive Science
A theoretical model describes, in a precise (formal) language, how we think that (a part of) cognition or behavior may work. When formulated as an algorithm, such models can even be implemented in a computer program and simulated. Simulated model behavior can then be compared with actual human behavior. A theoretical model is considered to be a “good” model to the extent that it helps us explain and understand cognitive and other psychological phenomena. In this course, students learn to build, simulate, test and evaluate your own theoretical models in any domain of interest in cognitive science or psychology.
For further details or to enroll, see the course guide. (This course was formerly known as Computational Formal Modeling.)
Blokpoel, M. & van Rooij, I. (2021). Theoretical modeling for cognitive science and psychology.
Cummins, R. (2000). “How does it work?” vs. “What are the laws?”: Two conceptions of psychological explanation. In Keil, F. and Wilson, R. (eds), Explanation and cognition. MIT Press.
Thagard, P. and Verbeurgt, K. (1998). Coherence as constraint satisfaction. Cognitive Science, 22: 1-24.
Hahn, U., Chater, N., & Richardson, L.B.C. (2003). Similarity as Transformation. Cognition, 87.
Master Thesis Coordinator
Cognition and Complexity
In this course, students learn to use methods derived from computational complexity theory for analyzing the (in)tractability of cognitive models, and for identifying sources of complexity in a model. Students also learn how this knowledge can be used to make model revisions that yield tractability. As two competing models may differ in the nature of their sources of complexity, the analyses can also yield novel empirical predictions that can be used to test the models.
For further details or to enroll, see the course guide.
van Rooij, I., Blokpoel, M., Kwisthout, J., Wareham, T. (2019). Intractability and Cognition: A guide to classical and parameterized complexity analysis. Cambridge: Cambridge University Press.
Analogical Abduction Proper (2016–2021) in Theoretical Foundations for Cognitive Agents
Cognitive Agent-based Modeling of Communication (2019–2021) in Social Neurocognition
Intractability of Models of Language Evolution (2021) in Cognition and Complexity
Intractability of Bayesian Action Understanding (2014–2015) in Cognition and Complexity