View By Topic:
All Topics
F Foundations
P Perception
E Education
CI Causal Induction
CD Cognitive Development
PR Probabilistic Reasoning
RPM Rational Process Models
S&C Similarity and Categorization
SML Statistical Models of Language
NBM Nonparametric Bayesian Models
CEIL Cultural Evolution and Iterated Learning
DMRL Decision Making and Reinforcement Learning

(Click on an author's name to view all papers by that author.)

Filter publications

By Agrawal, M.
Agrawal, M., Peterson, J. C., Cohen, J. D., & Griffiths, T. L. (2023). Stress, intertemporal choice, and mitigation behavior during the COVID-19 pandemic. Journal of Experimental Psychology: General, 152(9), 2695–2702. (pdf)
Peterson, J. C., Bourgin, D., Agrawal, M., Reichman, D., & Griffiths, T. (2021). Using large-scale experiments and machine learning to discover theories of human decision-making. Science, 372(6547), 1209-1214. (pdf)
Agrawal, M., Peterson, J. C., & Griffiths, T. L. (2020). Scaling up psychology via Scientific Regret Minimization. Proceedings of the National Academy of Sciences. (pdf)
Agrawal, M., Peterson, J. C., & Griffiths, T. L. (2019). Using machine learning to guide cognitive modeling: a case study in moral reasoning. Proceedings of the 41st Annual Conference of the Cognitive Science Society . (pdf)

© 2024 Computational Cognitive Science Lab  |  Department of Psychology  |  Princeton University