Mayrhofer, Ralf

General

I am a postdoctoral research scientist in my own research project “Agents and causes: Reconciling competing theories of causal reasoning” (DFG Ma 6545/1) at the Psychology Department of the University of Göttingen, Germany. The research project is part of the interdisciplinary priority program “New frameworks of rationality” (SPP 1516) of the Deutsche Forschungsgemeinschaft (DFG).

I studied psychology, economics, and business information systems. I obtained my PhD in psychology (minors: computational science and statistics) in 2009 within the interdisciplinary graduate program “Applied statistics and empirical methods” at the Center of Statistics (University of Göttingen).

Research interests

I am particularly interested in causal learning and reasoning, causal semantics, intuitive physics, categorization, and explanatory reasoning at the interdisciplinary boundaries of cognitive psychology, computer science, philosophy, and linguistics. To address my research questions, I typically combine experimental methods and mathematical modeling (esp. Bayesian modeling).

Teaching

I offer/offered (*) or co-organized courses in psychology and statistics, such as *Bayesian statistics, cognitive science (causal reasoning, causal perception), *scientific writing, *mathematical statistics, and experimental psychology.

Publications

 

  • Mayrhofer, R., & Waldmann, M. R. (2016). Sufficiency and necessity assumptions in causal structure induction. Cognitive Science, 40, 2137-2150. Full text
  • Waldmann, M. R., & Mayrhofer, R. (2016). Hybrid causal representations. In B. Ross (Ed.), The Psychology of Learning and Motivation (Vol. 65, pp. 85-127). New York: Academic Press. Full text
  • Mayrhofer, R., & Waldmann, M. R. (2016). Causal agency and the perception of force. Psychonomic Bulletin & Review, 23 (3), 789-796. Full text
  • Mayrhofer, R., & Waldmann, M. R. (2015). Agents and causes: Dispositional intuitions as a guide to causal structure. Cognitive Science, 39, 65-95. Full text

  • Meder, B., Mayrhofer, R., & Waldmann, M. R. (2014). Structure induction in diagnostic causal reasoning. Psychological Review, 121, 277-301. Full text

  • Mayrhofer, R., & Waldmann, M. R. (2014). Indicators of causal agency in physical interactions: The role of the prior context. Cognition, 132, 485-490. Full text

  • Neth, H., Engelmann, N., & Mayrhofer, R. (2014).  Foraging for alternatives: Ecological rationality in keeping options viable.  In P. Bello, M. Guarini, M. McShane, & B. Scassellati (Eds.), Proceedings of the 34th Annual Meeting of the Cognitive Science Society (pp. 1078-1083).  Austin, TX: Cognitive Science Society. Full text

  • Hagmayer, Y., & Mayrhofer, R. (2013). Hierarchical Bayesian models as formal models of causal reasoning. Argument & Computation, 4, 36-45.

  • Mayrhofer, R., & Waldmann, M. R. (2013). Agency intuitions in physical interactions. In M. Knauff, M. Pauen, N. Sebanz, & I. Wachsmuth (Eds.), Proceedings of the 35th Annual Conference of the Cognitive Science Society (pp. 996-1001). Austin, TX: Cognitive Science Society. Full text

  • Meder, B., & Mayrhofer, R. (2013). Sequential diagnostic reasoning with verbal information. In M. Knauff, M. Pauen, N. Sebanz, & I. Wachsmuth (Eds.), Proceedings of the 35th Annual Conference of the Cognitive Science Society (pp. 1014-1019). Austin, TX: Cognitive Science Society. Full text

  • Mayrhofer, R., & Rothe, A. (2012). Causal status meets coherence: The explanatory role of causal models in categorization. In N. Miyake, D. Peebles, & R. P. Cooper (Eds.), Proceedings of the 34th Annual Conference of the Cognitive Science Society (pp. 743–748). Austin, TX: Cognitive Science Society. Full text

  • Mayrhofer, R., & Waldmann, M. R. (2011). Heuristics in covariation-based induction of causal models: Sufficiency and necessity priors. In L. Carlson, C. Hölscher & T. Shipley (Eds.), Proceedings of the 33rd Annual Conference of the Cognitive Science Society (pp. 3110-3115). Austin, TX: Cognitive Science Society. Full text

  • Mayrhofer, R., Hagmayer, Y., & Waldmann, M. R. (2010). Agents and Causes: A Bayesian error attribution model of causal reasoning. In S. Ohlsson & R. Catrambone (Eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society (pp. 925-930). Austin, TX: Cognitive Science Society. Full text

  • Mayrhofer, R., Nagel, J., & Waldmann, M. R. (2010). The role of causal schemas in inductive reasoning. In S. Ohlsson & R. Catrambone (Eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society (pp. 1082-1087). Austin, TX: Cognitive Science Society. Full text

  • Griffiths, O., Mayrhofer, R., Nagel, J., & Waldmann, M. R. (2009). Causal schema-based inductive reasoning. In N. Taatgen, H. van Rijn, L. Schomaker & J. Nerbonne (Eds.), Proceedings of the 31st Annual Conference of the Cognitive Science Society (pp. 691-696). Austin, TX: Cognitive Science Society. Full text

  • Meder, B., Mayrhofer, R., & Waldmann, M. R. (2009). A rational model of elemental diagnostic inference. In N. Taatgen, H. van Rijn, L. Schomaker & J. Nerbonne (Eds.), Proceedings of the 31st Annual Conference of the Cognitive Science Society (pp. 2176-2181). Austin, TX: Cognitive Science Society. Full text

  • Mayrhofer, R., Goodman, N. D., Waldmann, M. R., & Tenenbaum, J. B. (2008). Structured correlation from the causal background. In B. C. Love, K. McRae, & V. M. Sloutsky (Eds.), Proceedings of the 30th Annual Conference of the Cognitive Science Society (pp. 303–308). Austin, TX: Cognitive Science Society. Full text