Computational Cognitive Science Lab

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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

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Decision Making and Reinforcement Learning
RPM DMRL	Cornell, C. A., Norman, K. A., Griffiths, T. L., & Zhang, Q. (in press). Improving memory search through model-based cue selection. Psychological Science. (preprint)
P DMRL	Dubey, R., Hardy, M., Griffiths, T., & Bhui, R. (in press). AI-generated visuals of car-free American cities help increase support for sustainable transport policies. Nature Sustainability. (preprint)
DMRL	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)
RPM DMRL	Callaway, F., Griffiths, T. L., & Karreskog, G. (2023). Rational heuristics for one-shot games. (preprint)
RPM DMRL	Callaway, F., Griffiths, T. L., Norman, K. A., & Zhang, Q. (2023). Optimal metacognitive control of memory recall. Psychological Review. (pdf)
RPM DMRL	Callaway, F., Hardy, M., & Griffiths, T. L. (2023). Optimal nudging for cognitively bounded agents: A framework for modeling, predicting, and controlling the effects of choice architectures. Psychological Review. (preprint)
NBM DMRL	Chang, M., Dayan, A. L., Meier, F., Griffiths, T. L., Levine, S., & Zhang, A. (2023). Neural Constraint Satisfaction: Hierarchical abstraction for combinatorial generalization in object rearrangement. Proceedings of the 11th International Conference on Learning Representations. (pdf)
RPM DMRL	Correa, C. G., Ho, M. K., Callaway, F., Daw, N. D., Griffiths, T. L. (2023). Humans decompose tasks by trading off utility and computational cost. PLOS Computational Biology, 19(6), e1011087. (pdf)
DMRL	Correa, C. G., Sanborn, S., Ho, M. K., Callaway, F., Daw, N. D., & Griffiths, T. L. (2023). Exploring the hierarchical structure of human plans via program generation. (preprint)
CEIL DMRL	Hardy, M. D., Thompson, B., Krafft, P. M., & Griffiths, T. L. (2023). Resampling reduces bias amplification in experimental social networks. Nature Human Behavior, 7, 2084-2098. (pdf)
DMRL	He, R., Correa, C. G., Griffiths, T. L., & Ho, M. K. (2023). Structurally guided task decomposition in spatial navigation tasks (Student Abstract). Proceedings of the AAAI Conference on Artificial Intelligence, 38. (pdf)
DMRL	Ho, M. K., Cohen, J. D., & Griffiths, T. L. (2023). Rational simplification and rigidity in human planning. Psychological Science, 34(11), 1281-1292. (pdf)
RPM DMRL	Jain, Y. R., Callaway, F., Griffiths, T. L., Dayan, P., He, R., Krueger, P. M., & Lieder, F. (2023). A computational process-tracing method for measuring people’s planning strategies and how they change over time. Behavior Research Methods, 55, 2037–2079. (pdf)
DMRL	Kumar, S., Dasgupta, I., Daw, N. D., Cohen, J. D., Griffiths, T. L. (2023). Disentangling abstraction from statistical pattern matching in human and machine learning. PLoS Computational Biology 19(8). (pdf)
DMRL	Oktar, K., Sucholutsky, I., Lombrozo, T., & Griffiths, T. L. (2023). Dimensions of disagreement: Unpacking divergence and misalignment in cognitive science and artificial intelligence. (preprint)
SML DMRL	Peng, A., Sucholutsky, I., Li, B., Sumers, T., Griffiths, T., Andreas, J., & Shah, J. (2023). Learning with language-guided state abstractions. RSS Workshop on Social Intelligence in Humans and Robots. (pdf)
DMRL	Peterson, J., Mancoridis, M., & Griffiths, T. (2023). To each their own theory: Exploring the limits of individual differences in decisions under risk. 45th Annual Meeting of the Cognitive Science Society. (pdf)
DMRL	Rane, S., Ho, M., Sucholutsky, I., & Griffiths, T. L. (2023). Concept alignment as a prerequisite for value alignment. AAAI 2024 Bridge on Collaborative AI and Modeling of Humans. (pdf)
RPM DMRL	Reichman, D., Lieder, F., Bourgin, D. D., Talmon, N., & Griffiths, T. L. (2023). The computational challenges of means selection problems: Network structure of Goal Systems predicts human performance. Cognitive Science, 47(8), e13330. (pdf)
DMRL	Russek, E., Callaway, F., & Griffiths, T. L. (2023). Inverting cognitive models with machine learning to infer preferences from fixations. Proceedings of the 39th Conference on Uncertainty in Artificial Intelligence. (pdf)
DMRL	Shin, M., Kim, J., van Opheusden, B., & Griffiths, T. L. (2023). Superhuman artificial intelligence can improve human decision-making by increasing novelty. Proceedings of the National Academy of Sciences, 120(12), e2214840120. (pdf)
DMRL	Sucholutsky, I., Muttenthaler, L., Weller, A., Peng, A., Bobu, A., Kim, B., Love, B. C., Grant, E., Achterberg, J., Tenenbaum, J. B., Collins, K. M., Hermann, K. L., Oktar, K., Greff, K., Hebart, M. N., Jacoby, N., Marjieh, R., Geirhos, R., Chen, S., Kornblith, S., Rane, S., Konkle, T., O'Connell, T. P., Unterthiner, T., Lampinen, A. K., Müller, K.-R., Toneva, M., & Griffiths, T. L. (2023). Getting aligned on representational alignment. (preprint)
RPM DMRL	Sukhov, N., Dubey, R., Duke, A., & Griffiths, T. (2023). When to keep trying and when to let go: Benchmarking optimal quitting. (preprint)
SML DMRL	Sumers, T. R., Ho, M. K., Griffiths, T. L., & Hawkins, R. D. (2023). Reconciling truthfulness and relevance as epistemic and decision-theoretic utility. Psychological Review. (pdf)
P DMRL	Turner, C. R., Morgan, T., & Griffiths, T. (2023). The joint evolution of sensory systems and decision policy allows cognition. 45th Annual Meeting of the Cognitive Science Society. (pdf)
DMRL	Xia, F., Zhu, J., & Griffiths, T. (2023). Comparing human predictions from expert advice to on-line optimization algorithms. 45th Annual Meeting of the Cognitive Science Society. (pdf)
SML DMRL	Yao, S., Yu, D., Zhao, J., Shafran, I., Griffiths, T. L., Cao, Y., & Narasimhan, K. (2023). Tree of thoughts: Deliberate problem solving with large language models. Advances in Neural Information Processing Systems, 37. (pdf)
RPM DMRL	Bai, X., Fiske, S. T., & Griffiths, T. L. (2022). Globally inaccurate stereotypes can result from locally adaptive exploration. Psychological Science, 33(5) 671–684. (pdf)
RPM DMRL	Callaway, F., Jain, Y. R., van Opheusden, B., Das, P., Iwama, G., Gul, S., Krueger, P. M., Becker, F., Griffiths, T. L., & Lieder, F. (2022). Leveraging artificial intelligence to improve people’s planning strategies. Proceedings of the National Academy of Sciences, 119(12), e2117432119. (pdf)
RPM DMRL	Callaway, F., van Opheusden, B., Gul, S., Das, P., Krueger, P. M., Griffiths, T. L., & Lieder, F. (2022). Rational use of cognitive resources in human planning. Nature Human Behaviour, 6, 1–14. (pdf)
F DMRL	Dubey, R., Griffiths, T. L., & Dayan, P. (2022). The pursuit of happiness: A reinforcement learning perspective on habituation and comparisons. PLoS Computational Biology, 18(8), e1010316. (pdf)
RPM DMRL	Ho, M. K., Abel, D., Correa, C. G., Littman, M. L., Cohen, J. D., & Griffiths, T. L. (2022). People construct simplified mental representations to plan. Nature, 606(7912), 129-136. (pdf)
F DMRL	Ho, M. K., & Griffiths, T. L. (2022). Cognitive science as a source of forward and inverse models of human decisions for robotics and control. Annual Review of Control, Robotics, and Autonomous Systems, 5, 33-53. (pdf)
SML DMRL	Kumar, S., Correa, C. G., Dasgupta, I., Marjieh, R., Hu, M. Y., Hawkins, R.D., Daw, N. D., Cohen, J. D., Narasimhan, K. R., & Griffiths, T. L. (2022). Using Natural Language and Program Abstractions to Instill Human Inductive Biases in Machines. Advances in Neural Information Processing Systems, 36. (preprint)
RPM DMRL	Russek, E., Acosta-Kane, D., van Opheusden, B., Mattar, M. G., & Griffiths, T. (2022). Time spent thinking in online chess reflects the value of computation. (preprint)
SML DMRL	Sumers, T. R., Hawkins, R. D., Ho, M. K., Griffiths, T. L., & Hadfield-Menell, D. (2022). How to talk so AI will learn: Instructions, descriptions, and autonomy. Advances in Neural Information Processing Systems, 36. (pdf)
RPM DMRL	Callaway, F., Rangel, A., & Griffiths, T. L. (2021). Fixation patterns in simple choice reflect optimal information sampling. PLOS Computational Biology, 17(3), e1008863. (pdf)
F E DMRL	Dubey, R., Ho, M. K., Mehta, H., & Griffiths, T. L. (2021). Aha! Moments correspond to meta-cognitive prediction errors. (preprint)
PR DMRL	Gates, V., Callaway, F., Ho, M. K., Griffiths, T. (2021). A rational model of people's inferences about others' preferences based on response times. Cognition, 217, 104885. (pdf)
DMRL	Kumar, S., Dasgupta, I., Cohen, J. D., Daw, N. D., & Griffiths, T. L. (2021). Meta-learning of structured task distributions in humans and machines. Proceedings of the 9th International Conference on Learning Representations (ICLR). (pdf)
RPM DMRL	Milli, S., Lieder, F., & Griffiths, T. L. (2021). A rational reinterpretation of dual-process theories. Cognition, 217, 104881. (pdf)
DMRL	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)
SML DMRL	Sumers, T. R., Hawkins, R. D., Ho, M. K., & Griffiths, T. L. (2021). Extending rational models of communication from beliefs to actions. Proceedings of the 43rd Annual Meeting of the Cognitive Science Society. (pdf)
SML DMRL	Sumers, T. R., Ho, M. K., Hawkins, R. D., Narasimhan, K. R., & Griffiths, T. L. (2021). Learning rewards from linguistic feedback. Proceedings of the 35th AAAI Conference on Artificial Intelligence. (pdf)
DMRL	Agrawal, M., Peterson, J. C., & Griffiths, T. L. (2020). Scaling up psychology via Scientific Regret Minimization. Proceedings of the National Academy of Sciences. (pdf)
DMRL	Alon, N., Cohen, J. D., Griffiths, T. L., Manurangsi, P., Reichman, D., Shinkar, I., Wagner, T., Yu, A. (2020). Multitasking capacity: Hardness results and improved constructions. SIAM Journal on Discrete Mathematics, 34(1), 885-903. (pdf)
RPM DMRL	Callaway, F., Hardy, M., & Griffiths, T. L. (2020). Optimal nudging. Proceedings of the 42nd Annual Conference of the Cognitive Science Society. (pdf)
DMRL	Chang, M., Kaushik, S., Weinberg, S. M., Griffiths, T., & Levine, S. (2020). Decentralized Reinforcement Learning: Global Decision-Making via Local Economic Transactions. Proceedings of the International Conference on Machine Learning. (pdf)
RPM DMRL	Correa, C. G., Ho, M. K., Callaway, F., & Griffiths, T. L. (2020). Resource-rational Task Decomposition to Minimize Planning Costs. Proceedings of the 42nd Annual Conference of the Cognitive Science Society. (pdf)
E DMRL	Dubey, R., & Griffiths, T. L. (2020). Reconciling novelty and complexity through a rational analysis of curiosity. Psychological Review, 127(3), 455-476. (pdf)
DMRL	Dubey, R., Grant, E., Luo, M., Narasimhan, K. R., & Griffiths, T. L. (2020). Connecting context-specific adaptation in humans to meta-learning. (preprint)
F DMRL	Gates, V., Griffiths, T. L., & Dragan, A. D. (2020). How to be helpful to multiple people at once. Cognitive Science, 44(6), e12841. (pdf)
DMRL	Ho, M. K., Abel, D., Cohen, J. D., Littman, M. L., & Griffiths, T. L. (2020). The Efficiency of Human Cognition Reflects Planned Information Processing. Proceedings of the 34th AAAI Conference on Artificial Intelligence. (pdf)
DMRL	Mormann, M., Griffiths, T. L., Janiszewski, C., Russo, J. E., Aribarg, A., Ashby, N. J., Bagchi, R., Bhatia, S., Kovacheva, M. M., & Mrkva, K. J. (2020). Time to pay attention to attention: using attention-based process traces to better understand consumer decision-making. Marketing Letters, 31, 381-392. (pdf)
P DMRL	Sumers, T. R., Ho, M. K., & Griffiths, T. L. (2020). Show or tell? Demonstration is more robust to changes in shared perception than explanation. Proceedings of the 42nd Annual Conference of the Cognitive Science Society. (pdf)
PR DMRL	Hardy, M., & Griffiths, T. L. (2019). Demonstrating the impact of prior knowledge in risky choice. (preprint)
DMRL	Lieder, F., Chen, O. X., Krueger, P. M., & Griffiths, T. L. (2019). Cognitive prostheses for goal achievement. Nature Human Behaviour, 3(10), 1096-1106. (pdf)
F DMRL	Ho, M. K., Abel, D., Griffiths, T. L., & Littman, M. L. (2019). The value of abstraction. Current Opinion in Behavioral Sciences, 29, 111-116. (pdf)
DMRL	Carroll, M., Shah, R., Ho, M. K., Griffiths, T., Seshia, S., Abbeel, P., & Dragan, A. (2019). On the Utility of Learning about Humans for Human-AI Coordination. In H. Wallach, H. Larochelle, A. Beygelzimer, F. Alché-Buc, E. Fox, & R. Garnett (Eds.), Advances in Neural Information Processing Systems, 32, 5174–5185. (pdf)
RPM DMRL	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)
PR DMRL	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)
DMRL	Bourgin, D., Peterson, J. C., 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)
RPM DMRL	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)
DMRL	Lieder, F., Callaway, F., Jain, Y. R., Krueger, P. M., Das, P., Gul, S., & Griffiths, T. L. (2019). A cognitive tutor for helping people overcome present bias. Proceedings of the Fourth Multidisciplinary Conference on Reinforcement Learning and Decision Making. (pdf)
RPM DMRL	Reichman, D., Lieder, F., Bourgin, D. D., Talmon, N., & Griffiths, T. L. (2018). The computational challenges of pursuing multiple goals: Network structure of goal systems predicts human performance. (preprint)https://psyarxiv.com/fqh3x/
RPM DMRL	Lieder, F., Shenhav, A., Musslick, S., & Griffiths, T.L. (2018). Rational metareasoning and the plasticity of cognitive control. PLoS Computational Biology, 14, e1006043. (pdf)
PR RPM DMRL	Lieder, F., Griffiths, T. L., Huys, Q. J. M., & Goodman, N. D. (2018). Empirical evidence for resource-rational anchoring and adjustment. Psychonomic Bulletin & Review, 25, 775-784. (pdf)
PR RPM DMRL	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, 25, 322-349. (pdf)
PR RPM DMRL	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)
RPM DMRL	Callaway, F., Gul, S., Krueger, P. M., Griffiths, T. L., & Lieder, F. (2018). Learning to select computations. Proceedings of the 35th Conference on Uncertainty in Artificial Intelligence. (pdf)
DMRL	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)
DMRL	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)
DMRL	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)
DMRL	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)
RPM DMRL	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)
PR RPM DMRL	Lieder, F., & Griffiths, T. L. (2017). Strategy selection as rational metareasoning. Psychological Review, 124(6), 762-794. (pdf)
PR DMRL	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)
DMRL	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)
RPM DMRL	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)