I have moved!>
I am now a postdoc in Todd Gureckis' lab at New York University. My new website is here, with my old site archived below.
I am interested in generative models and their role in thinking, reasoning and decision making. In particular, my research explores the idea that causally structured representations, or causal mental models, underlie many of the cognitive abilities that people (even psychologists) take for granted. These include our ability to imagine alternative states of the world, predict the consequences of our actions and generate explanations for the phenomena we encounter.Active causal learning
My PhD focuses on active causal learning. I explore how, through interactions with the environment and observations of its temporal dynamics, people are able to develop sophisticated causal models that they can recruit in inference, simulation and counterfactual reasoning. I show that interventional and temporal cues, along with top-down hierarchical constraints, can inform the the evolution and adaptation of increasingly rich causal models over extended experience. My research uses behavioural experimentation combined with computational and cognitive modelling to better understand how people build up these causal representations, exploring the bidirectional relationship between people's current beliefs and their active information gathering behaviour. We find that people exhibit a range of active causal learning strategies from the more heuristic exploration characteristic of children's play to highly controlled randomised controlled experiments of scientific research. A better understanding of how people learn and exploit causal models may help us explain reasoning fallacies and pathologies like superstition, hallucinations and depression, and has the potential to inform machine-learning research on active and unsupervised structure learning.Other areas of active research
Alongside work on active causal learning, I am involved with projects looking at: explanation in causal networks; active learning about physical properties e.g. masses and forces; optimal and greedy strategies for intervention or query selection; generalised information entropy measures; controlling complex causal systems containing delays and feedback loops.
I am also interested in philosophy of mind, particularly informational and functional theories of consciousness and in clarifying the relationship between phenomenology and thinking.
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Bramley, N. R., Mayrhofer, R., Gerstenberg, T. & Lagnado, D. A. (submitted). Causal learning from interventions and dynamics in continuous time.
Bramley, N. R., Gerstenberg, T., Mayrhofer, R. & Lagnado, D. A. (submitted). The role of time in causal learning.
Coenen, A., Bramley, N. R., Ruggeri, A. & Gureckis, T. M. (submitted). Beliefs about sparsity affect causal experimentation.
Schulz, E., Klenske, E. D., Bramley, N. R. & Speekenbrink, M. (submitted). Strategic exploration in human adaptive control.
Bramley, N. R., Dayan, P., Griffiths, T. L. & Lagnado, D. A. (2017). Formalizing Neurath's ship: Approximate algorithms for online causal learning. Psychological Review, to appear. preprint, supplementary materials
Bramley, N. R., Gerstenberg, T. & Tenenbaum, J. B. (2016). Natural Science: Active learning in dynamic physical microworlds. In Papafragou, A., Grodner, D., Mirman, D., & Trueswell, J.C. (Eds.) Proceedings of the 38th Annual Meeting of the Cognitive Science Society (pp. 2567 - 2572). Austin, TX: Cognitive Science Society. pdf, supplementary materials
McCormack, T., Bramley, N. R., Frosch, C., Patrick, F. & Lagnado, D. A. (2016). Children's Use of Interventions to Learn Causal Structure. Journal of Experimental Child Psychology. 141, 1-22. pdf
Bramley, N. R., Dayan, P. & Lagnado, D. A. (2015). Staying afloat on Neurath's boat: Heuristics for sequential causal learning. In Noelle, D. C. et al (Eds.) Proceedings of the 37th Annual Meeting of the Cognitive Science Society (pp. 262-267). Austin, TX: Cognitive Science Society. pdf, demo E1, demo E2
Bramley, N. R., Lagnado, D. A. & Speekenbrink, M. (2015). Conservative forgetful scholars: How people learn causal structure through interventions. Journal of Experimental Psychology: Learning, Memory & Cognition, Vol 41(3), 708-731. pdf, demo E1, demo E2, data
Bramley, N. R., Gerstenberg, T. & Lagnado, D. A (2014). The order of things: Inferring causal structure from temporal patterns. In P. Bello, M. Guarini, M. McShane, & B. Scassellati (Eds.), Proceedings of the 36th Annual Meeting of the Cognitive Science Society (pp. 236-242). Austin, TX: Cognitive Science Society. pdf, demo, data
Bramley, N. R., Nelson, J. D., Speekenbrink, M. Crupi, V., Lagnado, D. A. (2014). What should an active causal learner value? Poster presented at The Psychonomic Society Annual Meeting, Long Beach, California, USA. pdf
Bramley, N. R., Lagnado, D. A. & Speekenbrink, M. (2013). Mechanisms of active causal learning. Poster presented at The 35th Annual Meeting of the Cogntive Science Society, Berlin, Germany. pdf
Bramley, N. R. (2017). Constructing the world: Active causal learning in cognition. PhD thesis, Experimental Psychology, UCL, London. pdf
Bramley, N. R. (2013). Modelling active causal learning. MRes thesis, Computer science, UCL, London.
Bramley, N. R. (2011). Mechanisms of active causal learning. MSc thesis, Cognitive, Perceptual & Brain Sciences, UCL, London.
Bramley, N. R. (2009). Does physicalism entail panexperientialism? MA thesis, Philosophy, University of Glasgow.
Future-Minded: The Psychology of Agency and Control by Magda Osman. link
Until recently I hosted the London Judgment and Decision Making (LJDM) group seminar series, Wednesdays at 5pm, Room 313, 26 Bedford Way, UCL, WC1H 0AP. schedule
Causal learning in an imperfect world. For PSYC1103: Introduction to Psychological Experimentation, Experimental Psychology, UCL. 2014
Active physics learning demo
Left click on the objects to drag them around. Is A or B heavier? And do they attract or repel one another?
Neil Bramley, PhD student
Division of Psychology and Language Sciences
Room 2.01, 26 Bedford Way, WC1H 0AP
University College London, UK
E-mail: neil.bramley [at] ucl.ac.uk