I am a Chancellor's Fellow/Lecturer in the School of Informatics at the University of Edinburgh.
Research Interests: Computational models and empirical studies of inductive learning, with emphasis on cognitive development; causal inference; transfer learning and generalization; and Bayesian models.
Email: c.lucas@ed.ac.uk
CV: pdf
Humans have a remarkable ability to make inferences that go beyond the data available to them, using information gained in one context to shape judgments in another, and extrapolating from sparse information. They learn about attributes of people and things that cannot be directly observed, and acquire knowledge that aids subsequent learning. I study how people understand and solve these inductive problems. My specific interests are in higher-level cognition, including how people discover the causal structure of the world and how they understand the choices and preferences of others.
I am looking for Ph.D. students – see my note below.
Selected Publications
- Lucas, C. G., Griffiths, T. L., Williams, J. J., & Kalish,
M. L. (in press). A rational model of function learning. Psychonomic Bulletin and Review.
[link] - Lucas, C. G., Bridgers, S., Griffiths,
T. L., Gopnik, A. (2015).
When children are better (or at least more open-minded)
learners than adults: Developmental differences in learning
the forms of causal relationships.
Cognition, 131 (2): pp. 284-299
[link] [pdf] - Lucas, C. G., Griffiths, T. L., Xu, F., Fawcett, C., Gopnik, A. Kushnir, K., Markson, L., & Hu, J. (2014).
The Child as Econometrician: A Rational Model of Preference Understanding in Children. PLOS ONE.
[link] [pdf] - Lucas, C. G., Sterling, D. J., Kemp, C. (2012).
Superspace extrapolation reveals inductive biases in
function learning.
In N. Miyake, D. Peebles, & R. P. Cooper (Eds.),
Proceedings of the 34th Annual Conference of the
Cognitive Science Society (pp. 713–718). Austin, TX:
Cognitive Science Society.
[pdf] - Lucas, C. G., Kemp, C. (2012). A unified theory of counterfactual
reasoning. In N. Miyake, D. Peebles, & R. P. Cooper (Eds.),
Proceedings of the 34th Annual Conference of the Cognitive
Science Society (pp. 707–712). Austin, TX: Cognitive Science
Society.
[pdf] - Bes, B., Sloman, S., Lucas, C. G., & Raufaste, E. (2012). Non-Bayesian
Inference: Causal Structure Trumps Correlation.
Cognitive Science, 36: 1178-1203
[pdf] - Jern, A., Lucas, C. G., Kemp,
C. (2011). Evaluating the inverse decision-making approach
to preference learning.
In J. Shawe-Taylor,
R. S. Zemel, P. Bartlett, F. C. N Pereira, &
K. Q. Weinberger (Eds.), Advances in Neural Information
Processing Systems 24 (pp. 2276–2284).
[pdf] - Waisman, A. S., Lucas, C. G., Griffiths,
T. L. & Jacobs, L.F. (2011). A Bayesian model of
navigation in squirrels. In L. Carlson, C. Hlscher, &
T. Shipley (Eds.),
Proceedings of the 33rd Annual Conference of the Cognitive Science Society
(pp. 1274–1279). Austin, TX: Cognitive Science Society.
[pdf] - Lucas, C. G., & Griffiths, T. L. (2010).
Learning the form of causal relationships using hierarchical
Bayesian models. Cognitive Science , 34: 113–147
[pdf] - Kushnir, T., Gopnik, A., Lucas, C. G., &
Schulz, L. E. (2010).
Inferring hidden causal structure. Cognitive Science , 34: 148–160
[pdf] - Lucas, C. G., Gopnik, A., & Griffiths, T. L. (2010). Developmental
differences in learning the forms of causal
relationships. In S. Ohlsson & R. Catrambone (Eds.),
Proceedings of the 32nd Annual Conference of the Cognitive
Science Society (pp. 2852–2857). Austin, TX: Cognitive Science Society.
[pdf]
Teaching
Spring 2014: "Topics in Cognitive Modelling"
Information for prospective students
If you'd like to pursue a Ph.D. and might be interested in working with me, send me an email with some info about your research interests and academic background. It would be great if you could include a CV or a link to your homepage.
I'm happy to answer questions, and may be able to meet if you're around Edinburgh.
If you're not familiar with my research, you can take a look at some of my publications to get a sense of what I do. You can also see examples of Ph.D. project topics for my institute here.
It's a good idea to contact prospective supervisors sooner rather than later, because Edinburgh matches students to supervisors quite early, and more funding opportunities tend to be available if one starts earlier. It may also be helpful to note in your application that you are interested in working with me.