Recent advances in Cognitive Science, Computer Science and Mathematics, have resulted in the ability to develop computer programs that implement Probabilistic Cognitive Models (PCMs). The cognitive models that this course covers are based on approximate Bayesian Inference implemented by Markov Chain Monte Carlo and Variational techniques that have made this approach tractable. The objective of this course is to enable the student to develop models of cognition in a Bayesian framework.
| Spring | Summer | Fall | ||
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| 2023 | ||||
| 2022 | ||||
| 2021 |
Cognitive Modeling (4c)
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| 2020 |
Cognitive Modeling (4c)
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| 2019 |
Cognitive Modeling (4c)
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| 2018 |
Cognitive Modeling (4c)
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| 2017 |
Cognitive Modeling (4c)
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| 2016 |
Cognitive Modeling I (4c)
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| 2015 |
Cognitive Modeling I (4c)
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| 2014 | ||||
| 2013 |
Cognitive Modeling I (4c)
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| 2012 |
Cognitive Modeling I (4c)
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| 2011 |
Cognitive Modeling I (4c)
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| 2010 | ||||
| 2009 | ||||
| 2008 | ||||
| 2007 | ||||