Thomas Shultz (PhD Yale, Psychology) is Professor of Psychology and Associate Member of the School of Computer Science at McGill University. He teaches courses in Computational Psychology and Cognitive Science. He is a Fellow of the Canadian Psychological Association, and a founder and former Coordinator of McGill Cognitive Science. Research interests include connectionism, cognitive science, cognitive development, evolution and learning, and relations between knowledge and learning. He has over 390 research publications in these areas.
- Our preliminary paper on Converting Cascade-Correlation Neural Nets into Probabilistic Generative Models (Nobandegani & Shultz, 2017) was recently favorably reviewed by the In-Depth AI Technology & Industry Review. They were impressed by our efforts in "bestowing important human-like ... features such as knowledge and imagination to machines." Our paper also received an unusual 5/5 positive reviews from the highly competitive Cognitive Science annual conference; so we look forward to presenting a talk on this work at the July meeting in London.
- Dominique Danco won the best-poster award at the 12 April 2017 McGill Cognitive Science Undergraduate Research Presentation Day. She reported our work on how humanitarianism might compete more successfully with ethnocentrism in the evolution of cooperation.
- We have a new Publications section on Memory to showcase Peter Helfer's new models of memory reconsolidation.
- Our paper providing a novel resolution of Rogers' paradox about the inability of social learning to enhance population fitness appears in the February 2017 issue of Journal of Theoretical Biology. See the first item in RESEARCH HIGHLIGHTS for a quick summary of the major findings.
- Our paper on a neural implementation of Bayesian inference and learning appears in Cognitive Systems Research December 2016.
- Our paper reviewing the constructive neural-network approach to modeling psychological development was recently cited as an Editor's Choice publication in Cognitive Development.