Publications

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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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Rational Process Models
RPM
DMRL
Cornell, C. A., Norman, K. A., Griffiths, T. L., & Zhang, Q. (2024). Improving memory search through model-based cue selection. Psychological Science, 35 (1). (pdf)
RPM
DMRL
Mieczkowski, E., Turner, C. R., Vélez, N., & Griffiths, T. (2024). Explaining Social Loafing via Multiprocessing Efficiency. 46th Annual Meeting of the Cognitive Science Society. (pdf)
CD
RPM
Russek, E. M., Turner, C. R., McEwen, E., Miscov, A. M., Seed, A., & Griffiths, T. L. (2024). Modeling the Contributions of Capacity and Control to Working Memory Development. 46th Annual Meeting of the Cognitive Science Society. (pdf)
RPM
DMRL
Zhao, B., Velez, N., & Griffiths, T. L. (2024). A Rational Model of Innovation by Recombination. 46th Annual Meeting of the Cognitive Science Society. (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)
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)
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)
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)
RPM
DMRL
Sukhov, N., Dubey, R., Duke, A., & Griffiths, T. (2023). When to keep trying and when to let go: Benchmarking optimal quitting. (preprint)
RPM
Zhang, Q., Griffiths, T. L., & Norman, K. A. (2023). Optimal policies for free recall. Psychological Review, 130(4), 1104. (pdf)
RPM
Zhu, J. Q., Sanborn, A., Chater, N., & Griffiths, T. (2023). Computation-Limited Bayesian updating. 45th Annual Meeting of the Cognitive Science Society. (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)
RPM
S&C
Dasgupta, I., & Griffiths, T. L. (2022). Clustering and the efficient use of cognitive resources. Journal of Mathematical Psychology, 109, 102675. (pdf)
RPM
CEIL
Hardy, M. D., Krafft, P. M., Thompson, B., & Griffiths, T. L. (2022). Overcoming Individual Limitations Through Distributed Computation: Rational Information Accumulation in Multigenerational Populations. Topics in Cognitive Science, 14(3), 550–573. (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)
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)
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)
RPM
S&C
Devraj, A., Zhang, Q., & Griffiths, T.L. (2021). The dynamics of exemplar and prototype representations depend on environmental statistics. Proceedings of the 43rd Annual Conference of the Cognitive Science Society. (pdf)
RPM
DMRL
Milli, S., Lieder, F., & Griffiths, T. L. (2021). A rational reinterpretation of dual-process theories. Cognition, 217, 104881. (pdf)
PR
RPM
Wilson, S., Arora, S., Zhang, Q., & Griffiths, T.L. (2021). A rational account of anchor effects in hindsight bias. Proceedings of the 43th Annual Conference of the Cognitive Science Society. (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)
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)
F
RPM
Griffiths, T. L. (2020). Understanding human intelligence via human limitations. Trends in Cognitive Sciences, 24(11), 873-883. (pdf)
RPM
Lieder, F., & Griffiths, T. L. (2020). Resource-rational analysis: Understanding human cognition as the optimal use of limited computational resources. Behavioral and Brain Sciences, 43, e1. (pdf) (Response to Commentaries)
F
RPM
Griffiths, T. L., Callaway, F., Chang, M. B., Grant, E., Krueger, P. M., & Lieder, F. (2019). Doing more with less: meta-reasoning and meta-learning in humans and machines. Current Opinion in Behavioral Sciences, 29, 24-30. (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)
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)
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)
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)
CI
RPM
Bramley, N. R., Dayan, P., Griffiths, T. L., & Lagnado, D. A. (2017). Formalizing Neuraths Ship: Approximate algorithms for online causal learning. Psychological Review, 124(3), 301-338. (pdf)
RPM
Shenhav, A., Musslick, S., Lieder, F., Kool, W., Griffiths, T. L., Cohen, J. D., & Botvinick, M. M. (2017). Toward a rational and mechanistic account of mental effort. Annual Review of Neuroscience.(pdf)
RPM
Bourgin, D. D., Lieder, F., Reichman, D., Talmon, N., & Griffiths, T. L. (2017). The structure of goal systems predicts human performance. 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)
PR
RPM
Milli, S., Lieder, F., & Griffiths, T. L. (2017) When does bounded-optimal metareasoning favor few cognitive systems? Proceedings of the 31st AAAI Conference on Artificial Intelligence. (pdf)
RPM
Hsu, A. S., Horng, A., Griffiths, T. L., & Chater, N. (2016). When absence of evidence is evidence of absence: Rational inferences from absent data. Cognitive Science, 1-13. (pdf)
RPM
Lieder, F., & Griffiths, T. L. (2016). Helping people make better decisions using optimal gamification Proceedings of the 38th Annual Conference of the Cognitive Science Society. (pdf)
PR
RPM
Suchow, J. W., & Griffiths, T. L. (2016). Deciding to remember: Memory maintenance as a Markov Decision Process. Proceedings of the 38th Annual Conference of the Cognitive Science Society. (pdf)
RPM
SML
Abbott, J. T., Austerweil, J. L., & Griffiths, T. L. (2015). Random walks on semantic networks can resemble optimal foraging. Psychological Review, 122, 558-569. (pdf)
F
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Griffiths, T. L., Lieder, F., & Goodman, N. D. (2015). Rational use of cognitive resources: Levels of analysis between the computational and the algorithmic. Topics in Cognitive Science, 7, 217-229. (pdf)
CD
RPM
Gopnik, A., Griffiths, T. L., & Lucas, C. G. (2015). When younger learners can be better (or at least more open-minded) than older ones. Current Directions in Psychological Science, 24, 87-92. (pdf)
P
RPM
Hamrick, J., Smith, K. A., Griffiths, T. L., & Vul, E. (2015). Think again? The amount of mental simulation tracks uncertainty in the outcome. Proceedings of the 37th Annual Conference of the Cognitive Science Society (pdf)
PR
RPM
Lieder, F., & Griffiths, T. L. (2015). When to use which heuristic: A rational solution to the strategy selection problem. Proceedings of the 37th Annual Conference of the Cognitive Science Society. (pdf)
RPM
Lieder, F., Plunkett, D., Hamrick, J. B., Russell, S. J., Hay, N. J., & Griffiths, T. L. (2014). Algorithm selection by rational metareasoning as a model of human strategy selection. Advances in Neural Information Processing Systems, 27. (pdf)
CI
RPM
Bonawitz, E., Denison, S., Gopnik, A., & Griffiths, T. L. (2014). Win-stay, lose-sample,: A simple sequential algorithm for approximating Bayesian inference. Cognitive Psychology, 74, 35-65. (pdf)
PR
RPM
Vul, E., Goodman, N. D., Tenenbaum, J. B., & Griffiths, T. L. (2014). One and done? Optimal decisions from very few samples. Cognitive Science, 38, 599-637. (pdf)
RPM
SML
Bourgin, D. D., Abbott, J. T., Griffiths, T. L., Smith, K. A., & Vul, E. (2014). Empirical evidence for Markov chain Monte Carlo in memory search. Proceedings of the 36th Annual Conference of the Cognitive Science Society. (pdf)
PR
RPM
Hamrick, J. B., & Griffiths, T. L. (2014). What to simulate? Inferring the right direction for mental rotation. Proceedings of the 36th Annual Conference of the Cognitive Science Society. (pdf)
PR
RPM
Lieder, F., Hsu, M., & Griffiths, T. L. (2014). The high availability of extreme events serves resource-rational decision-making. Proceedings of the 36th Annual Conference of the Cognitive Science Society. (pdf)
RPM
Neumann, R., Rafferty, A. N., & Griffiths, T. L. (2014). A bounded rationality account of wishful thinking. Proceedings of the 36th Annual Conference of the Cognitive Science Society. (pdf)
RPM
Press, A., Pacer, M., Griffiths, T. L., & Christian, B. (2014). Caching algorithms and rational models of memory. Proceedings of the 36th Annual Conference of the Cognitive Science Society. (pdf)
CI
RPM
Denison, S., Bonawitz, E., Gopnik, A., & Griffiths, T. L. (2013). Rational variability in children's causal inferences: The Sampling Hypothesis. Cognition, 126, 285-300. (pdf)
PR
RPM
Abbott, J. T., Hamrick, J. B., & Griffiths, T. L. (2013). Approximating Bayesian inference with a sparse distributed memory system. Proceedings of the 35th Annual Conference of the Cognitive Science Society. (pdf)
RPM
SML
Abbott, J. T., Austerweil, J. L., & Griffiths, T. L. (2012). Human memory search as a random walk in a semantic network. Advances in Neural Information Processing Systems, 25. (pdf)
PR
RPM
Lieder, F., Griffiths, T. L., & Goodman, N. D. (2012). Burn-in, bias, and the rationality of anchoring. Advances in Neural Information Processing Systems, 25. (pdf)
CD
RPM
Bonawitz, E., Gopnik, A., Denison, S., & Griffiths, T. L. (2012). Rational randomness: The role of sampling in an algorithmic account of preschoolers' causal learning. In F. Xu (Ed.) Rational constructivism in cognitive development. Waltham, MA: Academic Press. (book)
F
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Griffiths, T. L., Vul, E., & Sanborn, A. N. (2012). Bridging levels of analysis for probabilistic models of cognition. Current Directions in Psychological Science, 21(4), 263-268. (pdf)
CI
RPM
Abbott, J. T., & Griffiths, T. L. (2011). Exploring the influence of particle filter parameters on order effects in causal learning. Proceedings of the 33rd Annual Conference of the Cognitive Science Society. (pdf)
CI
RPM
Bonawitz, E., Denison, S., Chen, A., Gopnik, A., & Griffiths, T. L. (2011). A simple sequential algorithm for approximating Bayesian inference. Proceedings of the 33rd Annual Conference of the Cognitive Science Society. (pdf)
RPM
S&C
NBM
Sanborn, A. N., Griffiths, T. L., & Navarro, D. J. (2010). Rational approximations to rational models: Alternative algorithms for category learning. Psychological Review, 117 (4), 1144-1167.(pdf)
PR
RPM
S&C
Shi, L., Griffiths, T. L., Feldman, N. H., & Sanborn, A. N. (2010). Exemplar models as a mechanism for performing Bayesian inference. Psychonomic Bulletin & Review, 17 (4), 443-464. (pdf)
PR
RPM
S&C
Sanborn, A. N., Griffiths, T. L., & Shiffrin, R. (2010). Uncovering mental representations with Markov chain Monte Carlo. Cognitive Psychology, 60, 63-106. (pdf)
CI
PR
RPM
Bonawitz, E. B., & Griffiths, T. L. (2010). Deconfounding hypothesis generation and evaluation in Bayesian models. Proceedings of the 32nd Annual Conference of the Cognitive Science Society. (pdf)
CI
PR
RPM
Denison, S., Bonawitz, E. B., Gopnik, A., & Griffiths, T. L. (2010). Preschoolers sample from probability distributions. Proceedings of the 32nd Annual Conference of the Cognitive Science Society. (pdf)
PR
RPM
Shi, L., & Griffiths, T. L. (2009). Neural implementation of hierarchical Bayesian inference by importance sampling. Advances in Neural Information Processing Systems 22. (pdf)
RPM
SML
Levy, R., Reali, F., & Griffiths, T. L. (2009). Modeling the effects of memory on human online sentence processing with particle filters. Advances in Neural Information Processing Systems 21. (pdf)
PR
RPM
Vul, E., Goodman, N. D., Griffiths, T. L., & Tenenbaum, J. B. (2009). One and done? Optimal decisions from very few samples. Proceedings of the 31st Annual Conference of the Cognitive Science Society. (pdf)
RPM
S&C
Shi, L., Feldman, N. H., & Griffiths, T. L. (2008). Performing Bayesian inference with exemplar models. Proceedings of the 30th Annual Conference of the Cognitive Science Society. (pdf)
RPM
S&C
NBM
Sanborn, A. N., Griffiths, T. L., & Navarro, D. J. (2006). A more rational model of categorization. Proceedings of the 28th Annual Conference of the Cognitive Science Society. (pdf)

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