Frédéric Dandurand
Software engineer for enterprise and research applications
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Research Areas

  • Machine learning (reinforcement, unsupervised and supervised)
  • Computational modeling of cognitive processes (problem solving and language)
  • Quantitative and experimental methods (detecting reliable maxima and spurts in noisy data, web-based experiments)

Selected Publications


For a complete list of publications (journal articles, conference papers, talks, seminar presentations and posters), select the appropriate menu item on the left.

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X X X Dandurand, F., & Shultz, T. R. (2014). A comprehensive model of development on the balance-scale Task. Cognitive Systems Research, 31-32, 1-25.
X X X Dandurand, F., Grainger, J., & Hannagan, T. (2013). Computational models of location-invariant orthographic processing. Connection Science, 25 (1), 1-26.
X X X Dandurand, F., Shultz, T. R., & Rey, A. (2012). Including cognitive biases and distance-based rewards in a connectionist model of complex problem solving. Neural Networks, 25, 41-56.
X X Dandurand, F., Grainger, J., Duñabeitia, J. A., & Granier, J.-P. (2011). On coding non-contiguous letter combinations. Frontiers in Psychology, 2(136), 1-12. doi:10.3389/fpsyg.2011.00136
X Dandurand, F., & Shultz, T. R. (2010). Automatic detection and quantification of growth spurts. Behavior Research Methods, 42(3), 809-823.
Automatic Maxima Detection (AMD) code for Matlab
X X X Hannagan, T., Dandurand, F., & Grainger, J. (2011). Broken symmetries in a location invariant word recognition network. Neural Computation, 23(1), 251-283.
X X X Dandurand, F., Grainger, J., & Dufau, S. (2010). Learning location invariant orthographic representations for printed words. Connection Science, 22(1), 25-42.
X X X Dandurand, F., & Shultz, T. R. (2009). Connectionist models of reinforcement, imitation, and instruction in learning to solve complex problems. IEEE Transactions on Autonomous Mental Development, 1(2), 110 - 121.
X X Dandurand, F., Shultz, T. R., & Onishi, K. H. (2008). Comparing online and lab methods in a problem-solving experiment. Behavior Research Methods, 40(2), 428-434.
Play version of the task described in the paper available at: http://lnsclab.org/members/Frederic.Dandurand/code/GizmoTask/
X X Dandurand, F., Berthiaume, V., & Shultz, T. R. (2007). A systematic comparison of flat and standard cascade-correlation using a student-teacher network approximation task. Connection Science, 19(3), 223-244.
X Dandurand F., & Lowther D. A. (1999). Electromagnetic device performance identification using knowledge based neural networks. IEEE Transactions on Magnetics, 35(3), 1817-1820.