Thomas Shultz (PhD Yale, Psychology) is Emeritus Professor of Psychology and Associate Member of the School of Computer Science at McGill University. He taught courses in Computational Psychology and Cognitive Science. He is a Fellow of the Canadian Psychological Association, and a founder and twice Director of the McGill Cognitive Science Programs. Research interests include cognitive science, cognitive development, evolution and learning, relations between knowledge and learning, decision making, problem solving, memory, neural networks, and agent-based modeling. He has over 440 research publications and over 8900 citations in these areas.

News:
  • Our paper simulating and explaining the learning and use of probability distributions in infants is in the November 2022 issue of Psychological Review. See an abstract under PUBLICATIONS  / Learning and development.
  • We presented five papers at the Cognitive Science conference last July (2022): one on simulating and explaining probability learning and use in chimpanzees and humans showing why humans are more successful than chimps, another showing that ingroup-biased copying promotes cultural diversity and complexity, and three on decision making (violation of cumulative independence, another on violation of stochastic dominance, and a third on using models  to train AI systems  faster and cheaper than training with humans). See more details under Learning and Decision making, respectively.
  • Marcel Montrey's paper explaining why humans prefer to copy in-group members is published in Psychological Science, June 2021. See an abstract under PUBLICATIONS  / Learning and development.
  • Our chapter on the Cascade-Correlation machine learning algorithm for the Encyclopedia of Machine Learning and Data Science is published online at Springer. See details under PUBLICATIONS / Neural networks.
  • Our chapter on Computational approaches to cognitive development: Bayesian and artificial-neural-network models  has been published in The Cambridge Handbook of Cognitive Development (pp. 318-338). Cambridge: Cambridge University Press.
  • Our paper on how human infants could learn and use probability distributions is published online at Psychological Review July 2021. See the abstract and link to the paper under PUBLICATIONS  / Learning and development.
  • Marcel Montrey's mathematical model showing how  humans' unique skills in hi-fidelity social learning  explains their unique ability for cumulative cultural evolution was published in the Proceedings of the Royal Society B  (June 2020). See the abstract and URL under PUBLICATIONS / Evolution.
  • Ardavan Nobandegani's article resolving the centuries-old St. Petersburg Paradox was published in Topics in Cognitive Science 2020. Our earlier paper on this topic won the award for Best Computational Modeling Paper on Higher-level Cognition at the 41st Annual Conference of the Cognitive Science Society, July 2019. This paradox concerns a lottery with infinite expected payoff, on which people are nevertheless willing to place only a very small bet. See the journal version published in Topics in Cognitive Science, under PUBLICATIONS / Decision making. Or RESEARCH HIGHLIGHTS / Resolving the St. Petersburg paradox.
  • Our article presenting a comprehensive systems model of memory reconsolidation and extinction was published in the journal Hippocampus:  Helfer, P. & Shultz, T. R. (2020). A computational model of systems memory reconsolidation and extinction. Hippocampus, 30, 659-677. See the Abstract and URL under PUBLICATIONS / Memory.