Publications

Working papers:
  • Binz, M. & Schulz, E. (submitted). Using cognitive psychology to understand GPT-3. [PDF]
  • Allen, K., Brändle, F., Botvinick, M., Fan, J.F., Gershman, S.J., Gopnik, A., Griffiths, T. L., Hartshorne, J.K., Hauser, T.U., Ho, M.K., de Leeuw, J.R., Ma, W.J., Murayama, K., Nelson, J.D., van Opheusden, B., Pouncy, T., Rafner, J., Rahwan, I., Rutledge, R., Sherson, J., Simsek, O., Spiers, H., Summerfield, C., Thalmann, M., Velez, N., Watrous, A, Tenenbaum, J.B. & Schulz, E. (submitted). Using Games to Understand the Mind.
  • Giron, A. P., Ciranka, S., Schulz, E., van den Bos, W., Ruggeri, A., Meder, B., & Wu, C. M. (submitted). Developmental changes in learning resemble stochastic optimization. [PDF]
  • Wu. S., Éltető, N., Dasgupta, I. & Schulz, E. (submitted). E pluribus unum but how? Chunking as a rational solution to the speed-accuracy trade-off. [PDF]
  • Binz, M. & Schulz, E. (submitted). Exploration With a Finite Brain. [PDF]
  • Brändle, F., Stocks, L.J., Tenenbaum, J.B., Gershman, S.J. & Schulz, E. (submitted). Intrinsically Motivated Exploration as Empowerment. [PDF]
  • Bertram, L., Schulz, E. & Nelson, J.D. (submitted). Subjective probability is modulated by emotions. [PDF]
  • Garvert, M.M., Saanum, T., Schulz, E., Schuck, N.W. & Doeller, C.F. (submitted). Hippocampal spatio-temporal cognitive maps adaptively guide reward generalization. [PDF]
  • Wu. S., Éltető, N., Dasgupta, I. & Schulz, E. (submitted). Learning Structure from the Ground Up: Hierarchical Representation Learning by Chunking. [PDF]
  • Otto, A.R., Devine, S., Schulz, E., Bornstein, A.M. & Louie, K. (submitted). Context-dependent choice and evaluation in real-world consumer behavior. [PDF]
  • Binz, M. & Schulz, E. (submitted). Reconstructing the Einstellung effect. [PDF]
  • Ruggeri, A., Pelz, M., Gopnik, A. & Schulz, E. (submitted). Toddlers search longer when there is more information to be gained. [PDF]
  • Jones, A., Schulz, E., Meder, B. & Ruggeri, A. (submitted). Learning functions actively. [PDF]

2022:
  • Dezza, I. C., Schulz, E., & Wu, C. M. (Eds., 2022). The Drive for Knowledge: The Science of Human Information-Seeking. Cambridge University Press.
  • Ludwig, T., Wu, C.M., & Schulz, E. (2022). Connecting Exploration, Generalization, and Planning in Correlated Trees. Proceedings of the 44th Annual Conference of the Cognitive Science Society. [PDF]
  • Demircan, C., Pettini, L, Saanum, T., Binz, M., Baczkowski, B., Doeller, C.F., Garvert, M.M. & Schulz, E. (2022). Decision-Making with Naturalistic Options. Proceedings of the 44th Annual Conference of the Cognitive Science Society. [PDF]
  • Wu, C.M., Schulz, E., Pleskac, T.J. & Speekenbrink, M. (2022). Time pressure changes how people explore and respond to uncertainty. Scientific Reports. [PDF]
  • Binz, M., Gershman, S.J, Schulz, E. & Endres, D. (2022). Heuristics from bounded meta-learned inference. Psychological Review. [PDF]
  • Brändle, F., Binz, M. & Schulz, E. (2022). Exploration beyond bandits. In I. C. Dezza, E. Schulz, & C. M. Wu (Eds.), The Drive for Knowledge: The Science of Human Information-Seeking. Cambridge: Cambridge University Press. [PDF]
  • Witte, K., Wise, T. & Schulz, E. (2022). The two faces of anxiety in exploration: Taking risks or playing it safe. The 5th Multidisciplinary Conference on Reinforcement Learning and Decision Making. [PDF]
  • Jagadish, A.K., Saanum, T., Wang, J.X., Binz, M. & Schulz, E. (2022). Probing Compositional Inference in Natural and Artificial Agents. The 5th Multidisciplinary Conference on Reinforcement Learning and Decision Making. [PDF]

2021:
  • Meder, B., Wu, C.M., Schulz, E. & Ruggeri, A. (2021). Development of directed and random exploration in children. Developmental Science, e13095. [PDF]
  • Tomov, M., Schulz, E. & Gershman, S.J. (2021). Multi-task reinforcement learning in humans. Nature Human Behaviour, 5, 764-773. [PDF].
  • Wu, C.M., Schulz, E. & Gershman, S.J. (2021). Inference and search on graph-structured spaces. Computational Brain and Behavior, 4, 125-147. [PDF]
  • Saanum, T., Schulz, E. & Speekenbrink, M. (2021). Compositional generalization in multi-armed bandits. Proceedings of the 43rd Annual Meeting of the Cognitive Science Society. [PDF]
  • Brändle, F., Allen, K.R., Tenenbaum, J.B. & Schulz, E. (2021). Using games to understand intelligence. Workshop at the 43rd Annual Conference of the Cognitive Science Society. [PDF] [Website]

2020:
  • Schulz, E. & Dayan, P. (2020). Computational psychiatry for computers. iScience. [PDF]
  • Wu, C.M., Schulz, E., Garvert, M.M., Meder, B. & Schuck, N.W. (2020). Similarities and differences in spatial and non-spatial cognitive maps. PLOS Computational Biology, 16, 1–28. [PDF]
  • Brändle, F., Wu, C.M. & Schulz, E. (2020). What are we curious about? Trends in Cognitive Sciences. [PDF]
  • Stojic, H., Schulz, E., Analytis, P.P. & Speekenbrink, M. (2020). It's new, but is it good? How generalization and uncertainty guide the exploration of novel options. Journal of Experimental Psychology: General. [PDF]
  • Schulz, E., Quiroga, F. & Gershman, S.J. (2020). Communicating compositional patterns. Open Mind, 4, 25-39. [PDF]
  • Dasgupta, I., Schulz, E., Tenenbaum, J.B. & Gershman, S.J. (2020). A theory of learning to infer. Psychological Review, 127, 412-441. [PDF]
  • Schulz, E., Franklin, N.T. & Gershman, S.J. (2020). Finding structure in multi-armed bandits. Cognitive Psychology, 119, 1-35. [PDF]
  • Bertram. L., Schulz, E., Hofer, M. & Nelson, J.D. (2020). The Psychology of Human Entropy Intuitions. Proceedings of the 42nd Annual Meeting of the Cognitive Science Society.[PDF]

2019:
  • Schulz, E., Wu, C.M., Ruggeri, A. & Meder, B. (2019). Searching for rewards like a child means less generalization and more directed exploration. Psychological Science. [PDF]
  • Schulz, E., Bhui, R. & Love, B.C., Brier, B., Todd, M.T. & Gershman, S.J. (2019). Structured, uncertainty-driven exploration in real-world consumer choice. Proceedings of the National Academy of Sciences, 116, 13903-13908. [PDF]
  • Schulz, E. & Gershman, S.J. (2019). The algorithmic architecture of exploration in the human brain. Current Opinion in Neurobiology, 55, 7-14. [PDF]
  • Wu, C.M., Schulz, E. & Gershman, S.J. (2019). Searching for rewards in graph-structured spaces. Proceedings of the Cognitive Computational Neuroscience Conference. [PDF]
  • Bertram, L., Schulz, E., Hofer, M. & Nelson, J.D. (2019). Entropy Mastermind: Learning from humans about intelligent systems. Human-like Computing Machine Intelligence Workshop. [PDF]
  • Wu, C.M., Schulz, E., Gerbaulet, K., Pleskac, T.J. & Speekenbrink, M. (2019). Under pressure: The influence of time limits on human exploration. Proceedings of the 41st Annual Conference of the Cognitive Science Society. [PDF]
  • Wu, C.M., Schulz, E. & Gershman, S.J. (2019). Generalization as diffusion: human function learning on graphs. Proceedings of the 41st Annual Conference of the Cognitive Science Society. [PDF]
  • Schulz, E., Bertram, L., Hofer, M. & Nelson, J.D. (2019). Exploring the space of human exploration using Entropy Mastermind. Proceedings of the 41st Annual Conference of the Cognitive Science Society. [PDF]
  • Dasgupta, I. Schulz, E., Hamrick, J.B. & Tenenbaum, J.B. (2019). Heuristics, hacks, and habits: Boundedly optimal approaches to learning, reasoning and decision making. Workshop at the 41th Annual Conference of the Cognitive Science Society. [PDF] [Website]

2018:
  • Wu, C.M., Schulz, E., Speekenbrink, M., Nelson, J.D., & Meder, B. (2018). Generalization guides human exploration in vast decision spaces. Nature Human Behaviour, 2, 915-924. [PDF]
  • Dasgupta, I., Schulz, E., Goodman, N.D. & Gershman, S.J. (2018). Remembrance of inferences past: amortization in human hypothesis generation. Cognition, 178, 67-81. [PDF]
  • Bramley, N.R., Schulz, E., Xu, F. & Tenenbaum, J.B. (2018). Learning as program indcution. Workshop at the 40th Annual Conference of the Cognitive Science Society. [PDF] [Website]
  • Rule, J., Schulz, E., Piantadosi, S.T. & Tenenbaum, J.B. (2018). Learning list concepts through program induction. Proceedings of the 40th Annual Conference of the Cognitive Science Society. [PDF]
  • Jones, A., Schulz, E., Meder, B. & Ruggeri, A. (2018). Active function learning. Proceedings of the 40th Annual Conference of the Cognitive Science Society. [PDF]
  • Krusche, M.J.F., Schulz, E., Guez, A. & Speekenbrink, M. (2018). Adaptive planning in human search. Proceedings of the 40th Annual Conference of the Cognitive Science Society. [PDF]
  • Wu, C.M., Schulz, E., Garvert, M.M., Meder, B. & Schuck, N.W. (2018). Connecting conceptual and spatial search via a model of generalization. Proceedings of the 40th Annual Conference of the Cognitive Science Society. [PDF]
  • Dasgupta, I., Smith, K.A., Schulz, E., Tenenbaum, J.B. & Gershman, S.J. (2018). Learning to act by integrating mental simulations and physical experiments. Proceedings of the 40th Annual Conference of the Cognitive Science Society. [PDF]
  • Schulz, E., Wu, C.M., Huys, Q.J.M., Krause, A. & Speekenbrink, M. (2018). Generalization and search in risky environments. Cognitive Science, 42, 2592-2620. [PDF]
  • Schulz, E., Speekenbrink, M. & Krause, A. (2018). A tutorial on Gaussian process regression: Modelling, exploring, and exploiting functions. Journal of Mathematical Psychology, 85, 1-16. [PDF]

2017:
  • Schulz, E., Tenenbaum, J.B., Duvenaud, D. Speekenbrink, M., & Gershman, S.J. (2017). Compositional Inductive Biases in Function Learning. Cognitive Psychology, 99, 44-79. [PDF]
  • Schulz, E., Konstantinidis, E. & Speekenbrink, M. (2017). Putting bandits into context: How function learning supports decision making. Journal of Experimental Psychology: Learning, Memory, and Cognition, 44, 927-943. [PDF]
  • Dasgupta, I., Schulz, E. & Gershman, S.J. (2017). Where do hypotheses come from? Cognitive Psychology, 96, 1-25. [PDF]
  • Schulz, E., Klenske, E.D., Bramley, N.R. & Speekenbrink, M. (2017). Strategic exploration in human adaptive control. Proceedings of the Thirty-Ninth Annual Conference of the Cognitive Science Society. [PDF]
  • Wu, C.M., Schulz, E., Speekenbrink, M., Nelson, J.D. & Meder, B. (2017). Mapping the unknown: The spatially correlated multi-armed bandit. Proceedings of the Thirty-Ninth Annual Conference of the Cognitive Science Society. [PDF]
  • Dasgupta, I., Schulz, E., Goodman, N.D. & Gershman, S.J. (2017). Amortized Hypothesis Generation. Proceedings of the Thirty-Ninth Annual Conference of the Cognitive Science Society. [PDF]
  • Schulz, E. (2017). Towards a unifying theory of generalization. PhD Thesis, University College London, Department of Experimental Psychology. [PDF]

2016:
  • Schulz, E., Speekenbrink, M., Hernández Lobato J. M., Ghahramani, Z. & Gershman, S.J. (2016). Quantifying mismatch in Bayesian optimization. NeurIPS Workshop on Bayesian Optimization: Black-box Optimization and beyond. [PDF]
  • Schulz, E., Tenenbaum, J.B., Duvenaud, D., Speekenbrink, M. & Gershman, S.J. (2016). Probing the Compositionality of Intuitive Functions. Advances in Neural Information Processing Systems, 29. [PDF]
  • Schulz, E., Huys, Q. J. M., Bach, D.R., Speekenbrink, M. & Krause, A. (2016). Better safe than sorry: Risky function exploitation through safe optimization. Proceedings of the Thirty-Eighth Annual Conference of the Cognitive Science Society. [PDF]
  • Schulz, E., Speekenbrink, M. & Meder, B. (2016). Simple trees in complex forests: Growing Take The Best by Approximate Bayesian Computation. Proceedings of the Thirty-Eighth Annual Conference of the Cognitive Science Society. [PDF]

2015:
  • Schulz, E., Konstantinidis, E. & Speekenbrink, M. (2015). Learning and decisions in contextual multi-armed bandit tasks. Proceedings of the Thirty-Seventh Annual Conference of the Cognitive Science Society. [PDF]
  • Schulz, E., Tenenbaum, J.B., Reshef, D.N., Speekenbrink, M. & Gershman, S.J. (2015). Assessing the perceived predictability of functions. Proceedings of the Thirty-Seventh Annual Conference of the Cognitive Science Society. [PDF]
  • Parpart, P., Schulz, E., Speekenbrink, M. & Love, B.C. (2015). Active learning as a means to distinguish among prominent decision strategies. Proceedings of the Thirty-Seventh Annual Conference of the Cognitive Science Society. [PDF]
  • Schulz, E., Konstantinidis, E. & Speekenbrink, M. (2015). Exploration-Exploitation in a Contextual Multi-Armed Bandit Task. Proceedings of the International Conference on Cognitive Modeling. [PDF]

Before 2015:
  • Schulz, E., Speekenbrink, M. & Shanks, D.R. (2014). Predict choice – a comparison of 21 mathematical models. Proceedings of the Thirty-Sixth Annual Conference of the Cognitive Science Society. [PDF]
  • Cokely, E.T., Ghazal, S., Galesic, M., Garcia-Retamero, R. & Schulz, E. (2013). How to measure risk comprehension in educated samples. Transparent Communication of Health Risks, 29-52. [PDF]
  • Cokely E.T., Galesic, M., Schulz, E., Ghazal, S. & Garcia-Retamero, R. (2012). Measuring risk literacy: The Berlin numeracy test. Judgment and Decision Making, 7, 25-47. [PDF]
  • Schulz,E., Cokely, E.T. & Feltz, A. (2011). Persistent bias in expert judgments about free will and moral responsibility: A test of the expertise defense. Consciousness and cognition, 20, 1722-1731. [PDF]