SCM: Schedule
Last updated: Oct 29 2025
| Date | Topic | Reading due BEFORE class |
| SEMESTER 1 | ||
| Tue, Sep 16 | Welcome and intro to SCM | <none> |
| Thu, Sep 18 | Intro to cognitive science | <none> |
| Tue, Sep 23 | Decoding a cogsci paper | Kunda, M., McGreggor, K., & Goel, A. K. (2013). A computational model for solving problems from the Raven’s Progressive Matrices intelligence test using iconic visual representations. Cognitive Systems Research, 22, 47-66. |
| Thu, Sep 25 | Theories, models, & evaluation | Thagard, P. (2005). Mind: Introduction to cognitive science. MIT press. Chapter 1. |
| Tue, Sep 30 | Knowledge representations | Tolman, E. C. (1948). Cognitive maps in rats and men. Psychological review, 55(4), 189. |
| Thu, Oct 02 | Knowledge representations | Markman, A. B. (1998). Knowledge representation. Psychology Press. Chapter 1. |
| Tue, Oct 07 | Culture & cognition | Henrich, J., Heine, S. J., & Norenzayan, A. (2010). The weirdest people in the world?. Behavioral and brain sciences, 33(2-3), 61-83. |
| Thu, Oct 09 | Culture & cognition | Tomasello, M. (1999). The Human Adaptation for Culture. Annual Review of Anthropology, 509-529. |
| Tue, Oct 14 | Cognitive architectures | Langley, P., Laird, J. E., & Rogers, S. (2009). Cognitive architectures: Research issues and challenges. Cognitive Systems Research, 10(2), 141-160. |
| Thu, Oct 16 | Cognitive architectures | Jones, R. M., Laird, J. E., Nielsen, P. E., Coulter, K. J., Kenny, P., & Koss, F. V. (1999). Automated intelligent pilots for combat flight simulation. AI magazine, 20(1), 27-27. |
| Tue, Oct 21 | Multiagent models | Balaji, P. G., & Srinivasan, D. (2010). An introduction to multi-agent systems. In Innovations in multi-agent systems and applications-1 (pp. 1-27). Berlin, Heidelberg: Springer Berlin Heidelberg. |
| Thu, Oct 23 | Multiagent models | Sun, R. (2001). Cognitive science meets multi-agent systems: A prolegomenon. Philosophical psychology, 14(1), 5-28. |
| Tue, Oct 28 | Neural networks | Nielsen, M. A. (2015). Neural networks and deep learning. Online book. Chapter 1. |
| Thu, Oct 30 | Neural networks | Nielsen, M. A. (2015). Neural networks and deep learning. Online book. Chapter 6. |
| Tue, Nov 04 | Graphical & Bayesian models | Perfors, A., Tenenbaum, J. B., Griffiths, T. L., & Xu, F. (2011). A tutorial introduction to Bayesian models of cognitive development. Cognition, 120(3), 302-321. |
| Thu, Nov 06 | Graphical & Bayesian models | Danks, D. (2014). Unifying the mind: Cognitive representations as graphical models. Mit Press. Chapter 3: A primer on graphical models |
| Tue, Nov 11 | Information theory | Stone, J. V. (2019). Information theory: A tutorial introduction. https://arxiv.org/pdf/1802.05968 |
| Thu, Nov 13 | Information theory | Sims, C. R. (2016). Rate–distortion theory and human perception. Cognition, 152, 181-198. |
| Tue, Nov 18 | Reinforcement learning | Sutton, R. S., & Barto, A. G. (1998). Reinforcement learning: An introduction. Cambridge: MIT press. Chapter 1. |
| Thu, Nov 20 | Reinforcement learning | Botvinick, M., Wang, J. X., Dabney, W., Miller, K. J., & Kurth-Nelson, Z. (2020). Deep reinforcement learning and its neuroscientific implications. Neuron, 107(4), 603-616. |
| Tue, Nov 25 | LLMs | Riedl, M. (2023). A Very Gentle Introduction to Large Language Models without the Hype. Medium. https://mark-riedl.medium.com/a-very-gentle-introduction-to-large-language-models-without-the-hype-5f67941fa59e |
| Thu, Nov 27 | LLMs | McCoy, R. T., Yao, S., Friedman, D., Hardy, M. D., & Griffiths, T. L. (2024). Embers of autoregression show how large language models are shaped by the problem they are trained to solve. Proceedings of the National Academy of Sciences, 121(41), e2322420121. |
| SEMESTER 2 | ||
| Tue, Jan 13 | Semester 2 welcome | <none> |
| Thu, Jan 15 | Visual communication | <none> |
| Tue, Jan 20 | Commentary | <none> |
| Thu, Jan 22 | Peer review | <none> |
| Tue, Jan 27 | class optional - essay Q&A | <none> |
| Thu, Jan 29 | class optional - essay Q&A | <none> |
| Fri, Jan 30 | essay due at 12:00pm noon | |
| Tue, Feb 03 | TBD | TBD |
| Thu, Feb 05 | TBD | TBD |
| Tue, Feb 10 | TBD | TBD |
| Thu, Feb 12 | TBD | TBD |
| Tue, Feb 17 | no class - flex learning week | |
| Thu, Feb 19 | no class - flex learning week | |
| Tue, Feb 24 | TBD | TBD |
| Thu, Feb 26 | TBD | TBD |
| Tue, Mar 03 | TBD | TBD |
| Thu, Mar 05 | TBD | TBD |
| Tue, Mar 10 | TBD | TBD |
| Thu, Mar 12 | TBD | TBD |
| Tue, Mar 17 | TBD | TBD |
| Thu, Mar 19 | TBD | TBD |
| Tue, Mar 24 | TBD | TBD |
| Thu, Mar 26 | TBD | TBD |
| Tue, Mar 31 | Professional topics | TBD |
| Thu, Apr 02 | SCM wrap-up | TBD |
License
Creative Commons - Attribution Non-Commercial