Publications

View By Topic:
All Topics
Foundations Foundations
Perception Perception
Education Education
Causal Induction Causal Induction
Cognitive Development Cognitive Development
Probabilistic Reasoning Probabilistic Reasoning
Rational Process Models Rational Process Models
Similarity and Categorization Similarity and Categorization
Statistical Models of Language Statistical Models of Language
Nonparametric Bayesian Models Nonparametric Bayesian Models
Cultural Evolution and Iterated Learning Cultural Evolution and Iterated Learning
Decision Making and Reinforcement Learning Decision Making and Reinforcement Learning

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

Decision Making and Reinforcement Learning
Rational Process Models
Decision Making and Reinforcement Learning
Agrawal, M., Peterson, J. C., & Griffiths, T. L. (preprint). Scaling up psychology via scientific regret minimization: A case study in moral decision-making. (link)
Probabilistic Reasoning
Decision Making and Reinforcement Learning
Hardy, M., & Griffiths, T. L. (preprint). Demonstrating the impact of prior knowledge in risky choice. (link)
Rational Process Models
Decision Making and Reinforcement Learning
Callaway, F., & Griffiths, T. L. (preprint). Attention in value-based choice as optimal sequential sampling. (link)
Decision Making and Reinforcement Learning
Lieder, F., Chen, O., & Griffiths, T. L. (preprint). Cognitive prostheses for goal achievement. (link)
Rational Process Models
Decision Making and Reinforcement Learning
Reichman, D., Lieder, F., Bourgin, D. D., Talmon, N., & Griffiths, T. L. (preprint). Goal pursuit for computationally bounded agents: The network structure of goal systems predicts human performance.
Rational Process Models
Decision Making and Reinforcement Learning
Milli, S., Lieder, F., & Griffiths, T. L. (preprint). A rational reinterpretation of dual process theories. (link)
Foundations
Decision Making and Reinforcement Learning
Ho, M. K., Abel, D., Griffiths, T. L., & Littman, M. L. (2019). The value of abstraction. Current Opinion in Behavioral Sciences. (pdf)
Rational Process Models
Decision Making and Reinforcement Learning
Chang, M. B., Gupta, A., Levine, S., & Griffiths, T. L. (2019). Automatically composing representation transformations as a means for generalization. Proceedings of the 7th International Conference on Learning Representations (ICLR) 2019. (pdf)
Probabilistic Reasoning
Decision Making and Reinforcement Learning
Ho, M. K., Korman, J., & Griffiths, T. L. (2019). The computational structure of unintentional meaning. Proceedings of the 41st Annual Conference of the Cognitive Science Society. (pdf)
Decision Making and Reinforcement Learning
Bourgin, D., Peterson, J., Reichman, D., Russell, S., & Griffiths, T. L. (2019). Cognitive model priors for predicting human decisions. Proceedings of the 36th International Conference on Machine Learning (ICML). (pdf)
Rational Process Models
Decision Making and Reinforcement Learning
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)
Rational Process Models
Decision Making and Reinforcement Learning
Callaway, F., Gul, S., Krueger, P. M., Griffiths, T. L., & Lieder, F. (2018). Learning to select computations. Uncertainty in Artificial Intelligence. (pdf)
Rational Process Models
Decision Making and Reinforcement Learning
Lieder, F., Shenhav, A., Musslick, S., & Griffiths, T.L. (2018). Rational metareasoning and the plasticity of cognitive control. PLoS Computational Biology. (pdf)
Probabilistic Reasoning
Rational Process Models
Decision Making and Reinforcement Learning
Lieder, F., Griffiths, T. L., Huys, Q. J. M., & Goodman, N. D. (2018). Empirical evidence for resource-rational anchoring and adjustment. Psychonomic Bulletin & Review. (pdf)
Probabilistic Reasoning
Rational Process Models
Decision Making and Reinforcement Learning
Lieder, F., Griffiths, T. L., Huys, Q. J. M., & Goodman, N. D. (2018). The anchoring bias reflects rational use of cognitive resources. Psychonomic Bulletin & Review. (pdf)
Probabilistic Reasoning
Rational Process Models
Decision Making and Reinforcement Learning
Lieder, F., Griffiths, T. L., & Hsu, M (2018). Over-representation of extreme events in decision making reflects rational use of cognitive resources. Psychological Review, 125(1), 1-32. (pdf)
Decision Making and Reinforcement Learning
Burns, K., Nematzadeh, A., Grant, E., Gopnik, A., & Griffiths, T. L. (2018). Exploiting attention to reveal shortcomings in memory models. Proceedings of the 2018 EMNLP Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP, 378-380. (pdf)
Decision Making and Reinforcement Learning
Dubey, R., Agrawal, P., Pathak, D., Griffiths, T. L., & Efros, A. A. (2018). Investigating human priors for playing video games. In Proceedings of the 35th International Conference on Machine Learning (ICML 2018). (pdf) (project website)
Decision Making and Reinforcement Learning
Krueger, P. M., & Griffiths, T. L. (2018). Shaping model-free habits with model-based goals. Proceedings of the 40th Annual Conference of the Cognitive Science Society. (pdf)
Decision Making and Reinforcement Learning
Sanborn, S., Bourgin, D. D., Chang, M., & Griffiths, T. L. (2018). Representational efficiency outweighs action efficiency in human program induction. Proceedings of the 40th Annual Conference of the Cognitive Science Society. (pdf)
Rational Process Models
Decision Making and Reinforcement Learning
Callaway, F., Lieder, F., Das, P., Gul, S., Krueger, P. M., & Griffiths, T. L. (2018). A resource-rational analysis of human planning. Proceedings of the 40th Annual Conference of the Cognitive Science Society. (pdf)
Probabilistic Reasoning
Rational Process Models
Decision Making and Reinforcement Learning
Lieder, F., & Griffiths, T. L. (2017). Strategy selection as rational metareasoning. Psychological Review, 124(6), 762-794. (pdf)
Probabilistic Reasoning
Decision Making and Reinforcement Learning
Fisac, J. F., Gates, M. A., Hamrick, J. B., Liu, C., Hadfield-Menell, D., Palaniappan, M., Malik, D., Sastry, S. S., Griffiths, T. L., & Dragan, A. D. (2017). Pragmatic-Pedagogic Value Alignment. International Symposium on Robotics Research. (pdf)
Decision Making and Reinforcement Learning
Krueger, P. M., Lieder, F., & Griffiths, T. L. (2017). Enhancing metacognitive reinforcement learning using reward structures and feedback. Proceedings of the 39th Annual Conference of the Cognitive Science Society. (pdf)
Rational Process Models
Decision Making and Reinforcement Learning
Lieder, F., Krueger, P. M., & Griffiths, T. L. (2017). An automatic method for discovering rational heuristics for risky choice. Proceedings of the 39th Annual Conference of the Cognitive Science Society. (pdf)

© 2019 Computational Cognitive Science Lab  |  Department of Psychology  |  Princeton University