Computational Approaches to Understanding Development

Leonidas Alex Doumas


University of Edinburgh

Lecture 1. Understanding Development and Computational Cognitive Science


  1. Halford, G. S. & Andrews, G. (2010). Information-processing models of cognitive development. In U. Gosami (Ed.) The Wiley-Blackwell Handbook of Childhood Cognitive Development, pp. 697-722.
  2. Marr D. (1982). Vision. Chapter 1.
  3. Wellman, H. M., & Gelman, S. A. (1998). Knowledge acquisition in foundational domains.

Supplemental readings (on Formal Properties of Computational Models)

  1. Doumas, L. A. A., & Hummel, J. E. (2012).  Computational models of higher-cognition. In K. J. Holyoak & R. G. Morrison (Eds.) The Oxford Handbook of Thinking and Reasoning. Oxford: Oxford University Press.

Lecture 2. Theories of Development and the Traditional Symbolic Approach


  1. David Klahr, Pat Langley and Robert T. Neches, (eds; 1987). Chapter 1 and Chapter 8. Production System Models of Learning and Development. 
  2. Plunkett, K., Karmiloff Smith, A., Bates, E., Elman, J. L., & Johnson, M. H. (1997).
  3. Connectionism and developmental psychology. Journal of Child Psychology and Psychiatry, 38(1), 53-80.


Lecture 3. Connectionist Approaches


  1. Elman, J. (2005). Connectionist models of cognitive development: Where next?. TICS. 
  2. Rogers, T. T., & McClelland, J. L. (2008). Précis of semantic cognition: A parallel distributed processing approach. Behavioral and Brain Sciences, 31(06), 689-714.

Lecture 4. Symbolic-connectionist Approaches


  1. Doumas. L. A. A., Hummel, J. E., & Sandhofer, C. M. (2008). A theory of the discovery and predication of relational concepts. Psychological Review, 115, 1 - 43.
  2. Hummel, J. E. (2010). Symbolic versus associative learning. Cognitive science, 34(6), 958-965.

Lecture 5. Bayesian Approaches


  1. Gopnik, A., & Wellman, H. M. (2012). Reconstructing constructivism: Causal models, Bayesian learning mechanisms, and the theory theory. Psychological bulletin, 138(6), 1085.
  2. Kemp, C., & Tenenbaum, J. B. (2008). The discovery of structural form. Proceedings of the National Academy of Sciences, 105(31), 10687-10692.
  3. 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.
  4. S.T. Piantadosi, J.B. Tenenbaum, and N.D Goodman. Bootstrapping in a language of thought: a formal model of numerical concept learning.Cognition, 123:199-217, 2012.