Hagmayer, York

Biografie

Forschung

Forschungschwerpunkte

  • Kausales Denken, Lernen und Entscheiden
  • Entscheiden und Urteilen in der angewandten Forschung

Kollaborationen

Lehre

Bachelorstudium

  • Quantitative Methoden 1 und 2

    Masterstudium

    • Evaluationsforschung
    • Vertiefung: Cognitive and Decision Sciences

    Publikationen

     

    • Von Sydow, M., Hagmayer, Y., & Meder, B. (2015). Transitive reasoning distorts induction in causal chains. Memory & Cognition, 43 (8), DOI 10.3758/s13421-015-0568-5.
    • Sirota, M., Juanchich, M. & Hagmayer, Y. (2014). Ecological rationality or nested sets? Individual differences in cognitive processing predict Bayesian reasoning. Psychonomic Bulletin & Review, 21, 198-214.
    • Hagmayer, Y. & Kostopoulou, O. (2013). A parallel constraint satisfaction model of information distortion in diagnostic reasoning. Proceedings of the 35th Annual Meeting of the Cognitive Science Society. Austin, TX: Cognitive Science Society.
    • Hagmayer, Y., & Kostopoulou, O. (2013). A constraint satisfaction model of information distortion. . In M. Knauff, M. Pauen, N. Sebanz & I. Wachsmuth (Eds.), Proceedings of the 35th Annual Conference of the Cognitive Science Society (531-536). Austin, TX: Cognitive Science Society.
    • Hagmayer, Y., & Meder, B. (2013). Repeated causal decision making. Journal of Experimental Psychology: Learning, Memory, and Cognition, 39, 33-50.
    • Waldmann, M. R., & Hagmayer, Y. (2013). Causal reasoning. In D. Reisberg (Ed.), Oxford Handbook of Cognitive Psychology (pp. 733-752). New York: Oxford University Press.
    • Hagmayer, Y. & Mayrhofer (2012). Hierarchical Bayesian models as formal models of causal reasoning. Argument & Computation, 4, 36-45.
    • Hagmayer, Y., & Osman, M. (2012). From colliding billiard balls to colluding housewives: Causal Bayes nets as rational models of everyday reasoning. Synthese, 189, 17-28.
    • Hagmayer, Y., Meder, B., von Sydow, M., & Waldmann, M. R. (2011). Category transfer in sequential causal learning: The unbroken mechanism hypothesis. Cognitive Science, 35, 842-873.
    • Mangold, S., & Hagmayer, Y. (2011). Unconscious vs. Conscious Thought in Causal Decision Making. In C. H. Carlson & T. Shipley (Eds.), Proceedings of the 33rd Annual Conference of the Cognitive Science Society (pp. 3104–3109). Austin, TX: Cognitive Science Society.
    • DeKwaadsteniet, L., Hagmayer, Y., Krol, N., & Wittman, C. (2010). Causal client models in selecting effective interventions: A cognitive mapping study. Psychological Assessment, 22(3), 581-592.
    • Hagmayer, Y., Meder, B., Osman, M., Mangold, S., & Lagnado, D. (2010). Spontaneous causal learning while controlling a dynamic system. Open Psychology Journal, 3, 145-162.
    • 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. Austin, TX: Cognitive Science Society.
    • Meder, B., Gerstenberg, T., Hagmayer, Y., & Waldmann, M. R. (2010). Observing and intervening: Rational and heuristic models of causal decision making. The Open Psychology Journal, 3, 119-135.
    • von Sydow, M., Hagmayer, Y., Meder, B., & Waldmann, M. R. (2010). How causal reasoning biases empirical evidence. In S. Ohlsson & R. Catrambone (Eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society (pp. 2087-2092). Austin, TX: Cognitive Science Society.
    • Sloman, S. A., Fernbach, P., & Hagmayer, Y. (2010). Self-Deception requires vagueness. Cognition. 115, 268-281.
    • Robinson, E. A., Sloman, S. A., Hagmayer, Y., & Herzog, C. K. (2010). Causality in solving economic problems. The Journal of Problem Solving (Internet-Ausgabe), 3, 106-130.
    • Meder, B., Hagmayer, Y., & Waldmann, M. R. (2009). The role of learning data in causal reasoning about observations and interventions. Memory & Cognition, 37, 249-264.
    • von Sydow, M., Meder, B., & Hagmayer, Y. (2009). A transitivity heuristic of probabilistic causal reasoning. In N.A. Taatgen & H. van Rijn (Eds.). In N. Taatgen, H. van Rijn, L. Schomaker & J. Nerbonne (Eds.), Proceedings of the 31st Annual Conference of the Cognitive Science Society (pp. 803-808). Austin, TX: Cognitive Science Society.
    • Hagmayer, Y., & Sloman, S. A. (2009). Decision makers conceive of their choice as intervention. Journal of Experimental Psychology: General, 138, 22-38.
    • Meder, B., & Hagmayer, Y. (2009). Causal induction enables adaptive decision making. Proceedings of the 31st Annual Conference of the Cognitive Science Society (pp.1651-1656). Austin, TX: Cognitive Science Society.
    • Hagmayer, Y. (2009). Investigating causal intuitions. In A. Gloeckner & C. Witteman (Hrsg.), Tracing intuitions (pp. 160-178). Cambridge, UK: Psychology Press.
    • Waldmann, M. R., Meder, B., von Sydow, M., & Hagmayer, Y. (2009). The tight coupling between category and causal learning. Cognitive Processing.
    • Waldmann, M. R., Cheng, P. W., Hagmayer, Y., & Blaisdell, A. P. (2008). Causal learning in rats and humans: a minimal rational model. In N. Chater & M. Oaksford (Eds.), The probabilistic mind. Prospects for Bayesian cognitive science (pp. 453-484). Oxford: Oxford University Press.
    • Hagmayer, Y., & Meder, B. (2008). Causal learning through repeated decision making. In B. C. Love, K. McRae, & V. M. Sloutsky (Eds.), Proceedings of the 30th Annual Conference of the Cognitive Science Society (pp. 179-184). Mahwah NJ: Erlbaum.
    • Hagmayer, Y., & Waldmann, M. R. (2008). Zur Rolle kausaler Mechanisman beim Lernen und Denken. In S. Pauen, D. Bailer-Jones & M. Dullstein (Eds.), Mechanismen und kausales Verstehen (S. 41-58). Heidelberg: Mentis.
    • Meder, B., Hagmayer, Y., & Waldmann, M. R. (2008). Inferring interventional predictions from observational learning data. Psychonomic Bulletin & Review, 15 (1), 75-80.
    • Hagmayer, Y., & Waldmann, M. R. (2007). Inferences about unobserved causes in human contingency learning. Quarterly Journal of Experimental Psychology, 60 (3), 330-355.
    • Lagnado, D. A., Waldmann, M. R., Hagmayer, Y., & Sloman, S. A. (2007). Beyond covariation: Cues to causal structure. In A. Gopnik, & L. Schulz (Eds.), Causal learing: Psychology, philosophy, and computation (pp.154-172).Oxford: Oxford University Press.
    • Hagmayer, Y., Sloman, S. A., Lagnado, D. A., & Waldmann, M. R. (2007). Causal reasoning through intervention. In A. Gopnik, & L. Schulz (Eds.), Causal learning: Psychology, philosophy, and computation (pp. 86-100). Oxford: Oxford University Press.
    • Waldmann, M. R., Hagmayer, Y., & Blaisdell, A. P. (2006). Beyond the information given: Causal models in learning and reasoning. Current Directions in Psychological Science, 15 (6), 307-311.
    • von Sydow, M., & Hagmayer, Y. (2006). Deontic logic and deontic goals in the Wason Selection Task. In R. Sun & N. Miyaki (Eds.), Proceedings of the Twenty-Eighth Annual Conference of the Cognitive Science Society, pp. 864-869). Mahwah, NJ: Erlbaum.
    • Sloman, S. A., & Hagmayer, Y. (2006). The causal psycho-logic of choice. Trends in Cognitive Science, 10, 407-412.
    • Hagmayer, Y., & Sloman, S. A. (2006). Causal vs. evidential decision making in Newcomb's Paradox. In R. Sun, & N. Miyake (Eds.), Proceedings of the Twenty-Eighth Annual Conference of the Cognitive Science Society. Mahwah, NJ: Erlbaum.
    • Hagmayer, Y., & Waldmann, M. R. (2006). Kausales Denken. In J. Funke (Hrsg.), Enzyklopädie der Psychologie "Denken und Problemlösen", Band C/II/8 (S. 87-166). Göttingen: Hogrefe Verlag.
    • Meder, B., Hagmayer, Y., & Waldmann, M. R. (2006). Understanding the causal logic of confounds. In R. Sun, & N. Miyake (Eds.), Proceedings of the Twenty-Eighth Annual Conference of the Cognitive Science Society (pp. 579-584). Mahwah, NJ: Erlbaum.
    • Waldmann, M. R., & Hagmayer, Y. (2006). Catagories and causality: The neglected direction. Cognitive Psychology, 53, 27-58.
    • Hagmayer, Y., & Sloman, S. A. (2005). A causal model theory of choice. In B. G. Bara, L. Barsalou, & M. Bucciarelli (Eds.), Proceedings of the Twenty-Seventh Annual Conference of the Cognitive Science Society (pp. 881-886). Mahwah, NJ: Erlbaum.
    • von Sydow, M., Hagmayer, Y., Metzner, N., & Waldmann, M. R. (2005). Cooperation detection and deontic reasoning in the Wason Selection Task. In K. Opwis, & I.-K. Penner (Eds.), Proceedings of KogWis05. The German Cognitive Science Society Conference 2005 (pp. 195-200). Basel: Schwabe.
    • Meder, B., Hagmayer, Y., & Waldmann, M. R. (2005). Doing after seeing. In B. G. Bara, L. Barsalou, & M. Bucciarelli (Eds.), Proceedings of the Twenty-Seventh Annual Conference of the Cognitive Science Society (pp. 1461-1466). Mahwah, NJ: Erlbaum.
    • Waldmann, M. R., & Hagmayer, Y. (2005). Seeing versus doing: Two modes of accessing causal knowledge and processing effort. Journal of Experimental Psychology: Learning, Memory, and Cognition, 31, 216-227
    • Hagmayer, Y., & Waldmann, M. R. (2004). Seeing the unobservable – Inferring the probability and impact of hidden causes. In K. D. Forbus, D. Gentner, & T. Regier (Eds.), Proceedings of the Twenty-Sixth Annual Conference of the Cognitive Science Society (pp. 523-528). Mahwah, NJ: Erlbaum.
    • Hagmayer, Y., & Waldmann, M. R. (2002). A constraint satisfaction model of causal learning and reasoning. Proceedings of the Twenty-Fourth Annual Conference of the Cognitive Science Society (pp. 405-410). Mahwah, NJ: Erlbaum.
    • Hagmayer, Y. & Waldmann, M. R. (2002). How temporal assumptions influence causal judgments. Memory & Cognition, 30, 1128-1137.
    • Waldmann, M. R., & Hagmayer, Y. (2001). Estimating causal strength: The role of structural knowledge and processing effort. Cognition, 82, 27-58.
    • Hagmayer, Y. (2001). Denken mit und über Kausalmodelle. Dissertationsschrift. [PDF]
    • Hagmayer, Y. & Waldmann, M. R. (2001). Testing complex causal hypotheses. In M. May and U. Oestermeier (Eds.). Interdisciplinary Perspectives on Causation. Bern Studies in the History and Philosophy of Science.
    • Hagmayer, Y. & Waldmann, M. R. (2000). Simulating causal models: The way to structural sensitivity. In Proceedings of the Twenty-Second Annual Conference of the Cognitive Science Society. (pp. 214-219). Mahwah, NJ: Erlbaum.
    • Hagmayer, Y., &. Waldmann, M. R. (1999). Sind statistische Verfahren adäquate Modelle kausalen Denkens? In M. May & U. Oestermeier (Hrsg.), KogWiss, 99. Workshop Kausalität. GMD Report, 60 (S. 39-43). St. Augustin.
    • Waldmann, M. R., & Hagmayer, Y. (1999). How categories shape causality. In Proceedings of the Twenty-first Annual Conference of the Cognitive Science Society. (pp. 761-766). Mahwah, NJ: Erlbaum.
    • Waldmann, M. R., & Hagmayer, Y. (1998). Die kognitive Konstruktion von Kausalität. Dialektik. Enzyklopädische Zeitschrift für Philosophie und Wissenschaften, 2, 101-114.
    • Waldmann, M. R., & Hagmayer, Y. (1995). Causal paradox: When a cause simultaneously produces and prevents an effect. In Proceedings of the Seventeenth Annual Conference of the Cognitive Science Society. (pp. 425-430). Mahwah, NJ: Erlbaum.