Selected Publications

  • Hamrick, J. B. & Mohamed, S. (2020). Levels of Analysis for Machine Learning. In Proceedings of the ICLR 2020 Workshop on Bridging AI and Cognitive Science.
    [abstract] [pdf] [video]

  • Hamrick, J. B., Bapst, V., Sanchez-Gonzalez, A., Pfaff, T., Weber, T., Buesing, L., & Battaglia, P. W. (2020). Combining Q-Learning and Search with Amortized Value Estimates. In Proceedings of the International Conference on Learning Representations (ICLR 2020).
    [abstract] [pdf] [video]

  • Bapst*, V., Sanchez-Gonzalez*, A., Doersch, C., Stachenfeld, K., Kohli, P., Battaglia, P. W., & Hamrick, J. B. (2019). Structured agents for physical construction. In Proceedings of the International Conference on Machine Learning (ICML 2019).
    [abstract] [pdf]

  • Hamrick, J. B. (2019). Analogues of mental simulation and imagination in deep learning. Current Opinion in Behavioral Sciences, 29, 8—16. doi: 10.1016/j.cobeha.2018.12.011
    [pdf]

  • Battaglia, P. W., Hamrick, J. B., Bapst, V., Sanchez-Gonzalez, A., Zambaldi, V., Malinowski, M., Tacchetti, A., Raposo, D., Santoro, A., Faulkner, R., Gulcehre, C., Song, F., Ballard, A., Gilmer, J., Dahl, G., Vaswani, A., Allen, K., Nash, C., Langston, V., Dyer, C., Heess, N., Wierstra, D., Kohli, P., Botvinick, M., Vinyals, O., Li, Y., & Pascanu, R. (2018). Relational inductive biases, deep learning, and graph networks. arXiv preprint arXiv:1806.01261.
    [abstract] [pdf]

  • Hamrick, J. B., Ballard, A. J., Pascanu, R., Vinyals, O., Heess, N., & Battaglia, P. W. (2017). Metacontrol for Adaptive Imagination-Based Optimization. In Proceedings of the 5th International Conference on Learning Representations (ICLR 2017).
    [abstract] [abstract] [pdf]

  • Battaglia, P. W., Hamrick, J. B., & Tenenbaum, J. B. (2013). Simulation as an engine of physical scene understanding. Proceedings of the National Academy of Sciences, 110(45), 18327—18332. doi: 10.1073/pnas.1306572110
    [abstract] [pdf+supplemental] [PNAS featured image]

    (see also the popular science articles from Scientific American and Fast Company)

All Publications

  • Parascandolo, G., Buesing, L., Merel, J., Hasenclever, L., Aslanides, J., Hamrick, J. B., Heess, N., Neitz, A., & Weber, T. (2020). Divide-and-Conquer Monte Carlo Tree Search For Goal-Directed Planning. arXiv preprint arXiv:2004.11410.
    [abstract] [pdf]

  • Kosoy, E., Collins, J., Chan, D. M., Hamrick, J. B., Huang, S., Gopnik, A., & Canny, J. (2020). Exploring Exploration: Comparing Children with RL Agents in Unified Environments. In Proceedings of the ICLR 2020 Workshop on Bridging AI and Cognitive Science.
    [abstract] [pdf] [video]

  • Bapst, V., Sanchez-Gonzalez, A., Shams, O., Stachenfeld, K., Battaglia, P. W., Singh, S., & Hamrick, J. B. (2019). Object-oriented state editing for HRL. In Proceedings of the NeurIPS 2019 Workshop on Perception as Generative Reasoning.
    [abstract] [pdf]

  • Project Jupyter, Blank, B., Bourgin, D., Brown, A., Bussonnier, M., Frederic, J., Granger, B., Griffiths, T. L., Hamrick, J. B., Kelley, K., Pacer, M, Page, L., Pérez, F., Ragan-Kelley, B., Suchow, J. W., & Willing, C. (2019). nbgrader: A Tool for Creating and Grading Assignments in the Jupyter Notebook. Journal of Open Source Education, 2(11), 32. doi: 10.21105/jose.00032
    [pdf] [review] [source]

  • Hamrick*, J. B., Allen*, K. R., Bapst, V., Zhu, T., McKee, K. R., Tenenbaum, J. B., & Battaglia, P. W. (2018). Relational inductive bias for physical construction in humans and machines. In Proceedings of the 40th Annual Conference of the Cognitive Science Society. Austin, TX: Cognitive Science Society.
    [abstract] [pdf]

  • Fisac, J. F., Gates, M. A., Hamrick, J. B., Liu, C., Hadfield-Menell, D., Palaniappan, M., Malik D., Sastry, S., Griffiths, T. L., & Dragan, A. D. (2017). Pragmatic-Pedagogic Value Alignment. In Proceedings of the International Symposium on Robotics Research (ISRR 2017). Winner of the Computing Community Consortium Blue Sky Award.
    [abstract] [pdf]

  • Hamrick, J. B. (2017). Metareasoning and Mental Simulation (Ph.D. thesis).
    [pdf]

  • Callaway, F., Hamrick, J. B., & Griffiths, T. L. (2017). Discovering simple heuristics from mental simulation. In G. Gunzelmann, A. Howes, T. Tenbrink, & E. J. Davelaar (Eds.), Proceedings of the 39th Annual Conference of the Cognitive Science Society. Austin, TX: Cognitive Science Society.
    [abstract] [pdf] [project page]

  • Fisac*, J. F., Liu*, C., Hamrick*, J. B., Sastry, S., Hedrick, J. K., Griffiths, T. L., & Dragan, A. D. (2016). Generating plans that predict themselves. In Proceedings of the 12th International Workshop on the Algorithmic Foundations of Robotics (WAFR 2016).
    *these authors contributed equally
    [pdf]

  • Hamrick, J. B., Pascanu, R., Vinyals, O., Ballard, A., Heess, N., & Battaglia, P. W. (2016). Imagination-Based Decision Making with Physical Models in Deep Neural Networks. In Proceedings of the NeurIPS 2016 Workshop on Intuitive Physics.
    [pdf]

  • Liu*, C., Hamrick*, J. B., Fisac*, J. F., Dragan, A. D., Hedrick, J. K., Sastry, S. S., & Griffiths, T. L. (2016). Goal Inference Improves Objective and Perceived Performance in Human-Robot Collaboration. In J. Thangarajah, K. Tuyls, C. Jonker, & S. Marsella (Eds.), Proceedings of the 15th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2016).
    *these authors contributed equally
    [pdf]

  • Hamrick, J. B., Battaglia, P. W., Griffiths, T. L., & Tenenbaum, J. B. (2016). Inferring Mass in Complex Scenes by Mental Simulation. Cognition, 157, 61–76. doi: 10.1016/j.cognition.2016.08.012
    [pdf] [project page]

  • Kluyver, T., Ragan-Kelley, B., Pérez, F., Granger, B., Bussonnier, M., Frederic, J., Kelley, K., Hamrick, J. B., Grout, J., Corlay, S., Ivanov, P., Avila, D., Abdalla, S., & Willing, C. (2016). Jupyter Notebooks—A publishing format for reproducible computational workflows. In Proceedings of the 20th International Conference on Electronic Publishing, 87–90.
    [pdf]

  • Hamrick, J. B. (2016). A Rejection Sampler. In M. DiBernardo & A. Brown (Eds.), The Architecture of Open Source Applications, Volume 4: 500 Lines or Less.
    [html]

  • Gureckis, T. M., Martin, J., McDonnell, J., Alexander, R. S., Markant, D. B., Coenen, A., Hamrick, J. B., & Chan, P. (2015). psiTurk: An open-source framework for conducting replicable behavioral experiments online. Behavioral Research Methods. doi: 10.3758/s13428-015-0642-8
    [pdf]

  • Goodman, N. D., Frank, M. C., Griffiths, T. L., Tenenbaum, J. B., Battaglia, P. W., & Hamrick, J. B. (2015). Relevant and Robust: A Response to Marcus and Davis (2013). Psychological Science, 26(4), 539–541. doi: 10.1177/0956797614559544
    [pdf]

  • Hamrick, J. B., Smith, K. A., Griffiths, T. L., & Vul, E. (2015). Think again? The amount of mental simulation tracks uncertainty in the outcome. In Proceedings of the 37th Annual Conference of the Cognitive Science Society. Austin, TX.
    [abstract] [pdf] [ppt slides]

  • 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. In Z. Ghahramani, M. Welling, C. Cortes, N. D. Lawrence, & K. Q. Weinberger (Eds.), Advances in Neural Information Processing Systems 27 (pp. 2870–2878).
    [abstract] [pdf]

  • Hamrick, J. B., & Griffiths, T. L. (2014). What to simulate? Inferring the right direction for mental rotation. In P. Bello, M. Guarini, M. McShane & B. Scassellati (Eds.), Proceedings of the 36th Annual Meeting of the Cognitive Science Society. Austin, TX.
    [abstract] [pdf] [html slides opens in new window]

  • Hamrick, J. B., & Griffiths, T. L. (2013). Mental Rotation as Bayesian Quadrature. In the Bayesian Optimization Workshop at NeurIPS 2013.
    [pdf] [poster]

  • Abbott, J. T., Hamrick, J. B., & Griffiths, T. L. (2013). Approximating Bayesian inference with a sparse distributed memory system. In M. Knauff, M. Pauen, N. Sebanz & I. Wachsmuth (Eds.), Proceedings of the 35th Annual Conference of the Cognitive Science Society. Austin, TX.
    [abstract] [pdf] [poster]

  • Hamrick, J. B. (2012). Physical Reasoning in Complex Scenes is Sensitive to Mass (Master’s thesis).
    [abstract] [pdf]

  • Hamrick, J. B., Battaglia, P. W., & Tenenbaum, J. B. (2011). Internal physics models guide probabilistic judgments about object dynamics. In L. Carlson, C. Holscher & T. Shipley (Eds.), Proceedings of the 33rd Annual Conference of the Cognitive Science Society. Austin, TX.
    [abstract] [pdf] [slides]