PhD HCC – Cognitive Science Reading List

Cognitive Science Qualifying Exam Reading List (PDFs)

June 15, 2021 

 

(1) Background textbook 

Thagard, P. (2005). MIND: An introduction to cognitive science, 2nd Edition. Cambridge, MA: MIT Press. 

 

(2) Computational theory of mind 

Turing, A. M. (1950). Computing machinery and intelligence. Mind, 49, 433-460. 

Newell, A., & Simon, H. A. (1976). Computer science as empirical inquiry: Symbols and search. Communications of the Association of Computing Machinery, 19, 113-126. 

 

(3) Levels of cognitive theory 

Marr, D. (1982). Vision: A computational investigation into the human representation and presentation of visual information. New York: W. H. Freeman. [chapter 1, pp. 8-31] 

 

(4) Philosophical debates 

Searle, J. R. (1980). Minds, brains, and programs. Behavioral and Brain Sciences, 3, 417-457. 

Fodor, J. A. (1983). Modularity of mind. Cambridge, MA: MIT Press. [pp. 44 (“Well then, what precisely…”) -101] Yuste, R. (2015). From the neuron doctrine to neural networks. Nature Reviews Neuroscience, 16, 1-11.

(5) Cognitive architecture: symbolic 

Laird, J. E., Lebiere, C., & Rosenbloom, P. S. (2017, Winter). A standard model of the mind: Toward a common computational framework across artificial intelligence, cognitive science, neuroscience, and robotics. AI Magazine, 13-26. 

Varma, S. (2016). The CAPS family of cognitive architectures. In S. E. F. Chipman (Ed.), The Oxford Handbook of Cognitive Science (pp. 49-68). Oxford University Press. 

 

(6) Cognitive architecture: neural networks 

Rumelhart, D. E. (1998). The architecture of mind: A connectionist approach. In P. Thagard (Ed.), Mind readings (pp. 207-238). Cambridge, MA: MIT Press. 

Hassabis, D., Kumaran, D., Summerfield, C., & Botvinick, M. (2017). Neuroscience-inspired artificial intelligence. Neuron, 95, 245-258. 

 

(7) Embodied, distributed, and situated cognition 

Wilson, M. (2002). Six views of embodied cognition. Psychonomic Bulletin & Review, 9, 625-636. 

Brooks, R. A. (1991). Intelligence without representation. Artificial Intelligence, 47, 139-159. 

 

(8) Social, cultural, and evolutionary approaches 

Tomasello, M. (2000) The Cultural Origins of Human Cognition [chapters 1-3] 

 

(9) Problem solving and expertise 

Robertson, S. I. (2017). Problem solving: Perspectives from cognition and neuroscience (2nd ed.). London: Routledge. [well-structured problem solving, pp. 27-53; insight problem solving, pp. 176-204; analogical problem solving, pp. 66-88] 

Bransford, J. D., Brown, A. L., & Cocking, R. R. (2000). How people learn: Brain, mind, experience, and school. Washington, DC: National Academy Press. [chapter 2: expertise] 

 

(10) Similarity and analogy 

Goldstone, R. L., & Son, J. Y. (2012). Similarity. In K. J. Holyoak & R. G. Morrison (Eds.), The Oxford handbook of thinking and reasoning (p. 155–176). Oxford University Press. 

Gentner, D., & Smith, L. A. (2013). Analogical learning and reasoning. In D. Reisberg (Ed.), The Oxford handbook of cognitive psychology (p. 668–681). Oxford University Press. 

Kunda, M., McGreggor, K., & Goel, A. (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. 

 

(11) Concepts and knowledge representation 

Murphy, G. L. (2002). The big book of concepts. Cambridge, MA: MIT Press. [chapters 2 and 3] 

Carey, S. (2014). On learning new primitives in the language of thought: Reply to Reys. Mind & Language, 29, 133-166. 

Markman, A. B. (2002). Knowledge representation. In H. Pashler & D. Medin (Eds.), Steven's handbook of experimental psychology: Memory and cognitive processes (pp. 165–208). XXX: Wiley. 

 

(12) Metaphor and blending 

Fauconnier, G. (2001). Conceptual blending and analogy. In D. Gentner, K. J. Holyoak, & B. N. Kokinov (Eds.), The analogical mind: Perspectives from cognitive science (pp. 255-285). Cambridge, MA: MIT Press. 

Lakoff, G., & Johnson, M. (1980). Metaphors we live by. Chicago, IL. The University of Chicago Press. 

 

(13) Creativity 

Davis, N., Hsiao, C., Singh, K., Lin, B., & Magerko, B. (2017). Creative sense-making: quantifying interaction dynamics in co-creation. Proceedings of the 11th Conference on Creativity and Cognition, Singapore. 

Kaufman, J. C., & Glaveanu, V. P. (2019). A review of creativity theories: What questions are we trying to answer? In J. C. Kaufman & R. J. Sternberg (Eds.), The Cambridge handbook of creativity, 2nd Edition (pp. 27-43). Cambridge University Press.