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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

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Rational Process Models
Foundations
Probabilistic Reasoning
Rational Process Models
Lieder, F., & Griffiths, T. L. (in press). Strategy selection as rational metareasoning. Psychological Review. (pdf)
Probabilistic Reasoning
Rational Process Models
Lieder, F., Griffiths, T. L., & Hsu, M. (in press). Over-representation of extreme events in decision making reflects rational use of cognitive resources. Psychological Review. (pdf)
Probabilistic Reasoning
Rational Process Models
Lieder, F., Griffiths, T. L., Huys, Q. J. M., & Goodman, N. D. (in press). Empirical evidence for resource-rational anchoring and adjustment. Psychonomic Bulletin & Review. (pdf)
Probabilistic Reasoning
Rational Process Models
Lieder, F., Griffiths, T. L., Huys, Q. J. M., & Goodman, N. D. (in press). The anchoring bias reflects rational use of cognitive resources. Psychonomic Bulletin & Review. (pdf)
Causal Induction
Rational Process Models
Bramley, N. R., Dayan, P., Griffiths, T. L., & Lagnado, D. A. (in press). Formalizing Neuraths Ship: Approximate algorithms for online causal learning. Psychological Review. (pdf)
Probabilistic Reasoning
Rational Process Models
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)
Rational Process Models
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)
Rational Process Models
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)
Probabilistic Reasoning
Rational Process Models
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)
Rational Process Models
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)
Perception
Rational Process Models
Hamrick, J. B., 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)
Probabilistic Reasoning
Rational Process Models
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)
Rational Process Models
Statistical Models of Language
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)
Foundations
Rational Process Models
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)
Cognitive Development
Rational Process Models
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)
Rational Process Models
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)
Rational Process Models
Statistical Models of Language
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)
Probabilistic Reasoning
Rational Process Models
Hamrick, J., & 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)
Probabilistic Reasoning
Rational Process Models
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)
Rational Process Models
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)
Rational Process Models
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)
Causal Induction
Rational Process Models
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)
Probabilistic Reasoning
Rational Process Models
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)
Causal Induction
Rational Process Models
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)
Probabilistic Reasoning
Rational Process Models
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)
Rational Process Models
Statistical Models of Language
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)
Probabilistic Reasoning
Rational Process Models
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)
Cognitive Development
Rational Process Models
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)
Foundations
Rational Process Models
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)
Causal Induction
Rational Process Models
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)
Causal Induction
Rational Process Models
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)
Rational Process Models
Similarity and Categorization
Nonparametric Bayesian Models
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)
Probabilistic Reasoning
Rational Process Models
Similarity and Categorization
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)
Causal Induction
Probabilistic Reasoning
Rational Process Models
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)
Causal Induction
Probabilistic Reasoning
Rational Process Models
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)
Probabilistic Reasoning
Rational Process Models
Similarity and Categorization
Sanborn, A. N., Griffiths, T. L., & Shiffrin, R. (2010). Uncovering mental representations with Markov chain Monte Carlo. Cognitive Psychology, 60, 63-106. (pdf)
Probabilistic Reasoning
Rational Process Models
Shi, L., & Griffiths, T. L. (2009). Neural implementation of hierarchical Bayesian inference by importance sampling. Advances in Neural Information Processing Systems 22. (pdf)
Probabilistic Reasoning
Rational Process Models
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)
Rational Process Models
Statistical Models of Language
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)
Rational Process Models
Similarity and Categorization
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)
Rational Process Models
Similarity and Categorization
Nonparametric Bayesian Models
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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