Bridging AI and Cognitive Science (BAICS)
April 26, 2020
This page contains a non-exhaustive, community-curated list of resources for machine learning practitioners to learn more about cognitive science. Please feel free to contact Jess Hamrick if you would like to suggest other resources to be added, or submit a PR on GitHub.
- Gopnik, A., & Wellman, H. M. (1992). Why the child's theory of mind really is a theory. Mind & Language, 7(1‐2), 145-171.
- Tomasello, M., Carpenter, M., Call, J., Behne, T., & Moll, H. (2005). Understanding and sharing intentions: The origins of cultural cognition. Behavioral and brain sciences, 28(5), 675-691.
- Johnson-Laird, P. N. (2010). Mental models and human reasoning. Proceedings of the National Academy of Sciences, 107(43), 18243-18250.
- Gentner, D., & Smith, L. (2012). Analogical reasoning. Encyclopedia of human behavior, 130, 130.
- Tenenbaum, J. B., Kemp, C., Griffiths, T. L., & Goodman, N. D. (2011). How to grow a mind: Statistics, structure, and abstraction. science, 331(6022), 1279-1285.
- Griffiths, T. L., & Tenenbaum, J. B. (2009). Theory-based causal induction. Psychological review, 116(4), 661.
- Gopnik, A., Meltzoff, A. N., & Bryant, P. (1997). Words, thoughts, and theories (Vol. 1). MIT Press.
- Carey, S. (2009). The origin of concepts. Oxford university press.
- Murphy, G. (2004). The big book of concepts. MIT press.
- Chemero, A. (2011). Radical embodied cognitive science. MIT press.