SCM: Schedule
Last updated: Oct 29 2025
| Date | Topic | Reading due BEFORE class |
| Tue, Sep 22 | Welcome and intro to SCM | <none> |
| Thu, Sep 24 | Intro to cognitive science | <none> |
| Tue, Sep 29 | Representations | Thagard, P. (2005). Mind: Introduction to cognitive science. MIT press. Chapter 1. |
| Thu, Oct 01 | Representations | Zhao, B., Lucas, C. G., & Bramley, N. R. (2024). A model of conceptual bootstrapping in human cognition. Nature Human Behaviour, 8(1), 125-136. |
| Tue, Oct 06 | 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, Oct 08 | Bayesian models | Griffiths, T. L., Zhu, J. Q., Grant, E., & Thomas McCoy, R. (2024). Bayes in the age of intelligent machines. Current Directions in Psychological Science, 33(5), 283-291. |
| Tue, Oct 13 | Neural network models | Nielsen, M. A. (2015). Neural networks and deep learning. Online book. Chapter 1 (omit 1.6 "Implementing our network") |
| Thu, Oct 15 | Neural network models | Nielsen, M. A. (2015). Neural networks and deep learning. Online book. Chapter 6. |
| Tue, Oct 20 | Neuro-symbolic models | McCoy, R. T., & Griffiths, T. L. (2025). Modeling rapid language learning by distilling Bayesian priors into artificial neural networks. Nature communications, 16(1), 4676. |
| Thu, Oct 22 | Neuro-symbolic models | Mao, J., et al. (2019) The neuro-symbolic concept learner: Interpreting scenes, words, and sentences from natural supervision. ICLR. |
| Tue, Oct 27 | Culture & cognition | Tomasello, M. (1999). The Human Adaptation for Culture. Annual Review of Anthropology, 509-529. |
| Thu, Oct 29 | 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. |
| Tue, Nov 03 | Efficient encoding | Kemp, C., Xu, Y., & Regier, T. (2018). Semantic typology and efficient communication. Annual Review of Linguistics, 4, 109-128. |
| Thu, Nov 05 | Efficient encoding | Sims, C. R. (2016). Rate–distortion theory and human perception. Cognition, 152, 181-198. |
| Tue, Nov 10 | Cultural transmission | Kalish, M. L., Griffiths, T. L., & Lewandowsky, S. (2007). Iterated learning: Intergenerational knowledge transmission reveals inductive biases. Psychonomic bulletin & review, 14(2), 288-294. |
| Thu, Nov 12 | Cultural transmission | Shumailov, Ilia, et al. (2024) AI models collapse when trained on recursively generated data. Nature 631.8022: 755-759. |
| Tue, Nov 17 | Reinforcement learning | Sutton, R. S., & Barto, A. G. (1998). Reinforcement learning: An introduction. Cambridge: MIT press. Chapter 1. |
| Thu, Nov 19 | 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 24 | LLMs | Binz, M., et al. (2025). A foundation model to predict and capture human cognition. Nature, 1-8. |
| Thu, Nov 26 | LLMs | Castro et al. (2025) Discovering symbolic cognitive models from human and animal behavior. bioRxiv. |
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