14 found
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  1.  29
    Causal Reasoning Through Intervention.York Hagmayer, Steven A. Sloman, David A. Lagnado & Michael R. Waldmann - 2007 - In Alison Gopnik & Laura Schulz (eds.), Causal Learning: Psychology, Philosophy, and Computation. Oxford University Press.
  2.  4
    Decision Makers Conceive of Their Choices as Interventions.York Hagmayer & Steven A. Sloman - 2009 - Journal of Experimental Psychology: General 138 (1):22-38.
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  3.  22
    Beyond Covariation.David A. Lagnado, Michael R. Waldmann, York Hagmayer & Steven A. Sloman - 2007 - In Alison Gopnik & Laura Schulz (eds.), Causal Learning: Psychology, Philosophy, and Computation. Oxford University Press.
  4.  45
    The Causal Psycho-Logic of Choice.Steven A. Sloman & York Hagmayer - 2006 - Trends in Cognitive Sciences 10 (9):407-412.
  5.  39
    Causal Bayes Nets as Psychological Theories of Causal Reasoning: Evidence From Psychological Research.York Hagmayer - 2016 - Synthese 193 (4):1107-1126.
    Causal Bayes nets have been developed in philosophy, statistics, and computer sciences to provide a formalism to represent causal structures, to induce causal structure from data and to derive predictions. Causal Bayes nets have been used as psychological theories in at least two ways. They were used as rational, computational models of causal reasoning and they were used as formal models of mental causal models. A crucial assumption made by them is the Markov condition, which informally states that variables are (...)
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  6.  18
    Self-Deception Requires Vagueness.Steven A. Sloman, Philip M. Fernbach & York Hagmayer - 2010 - Cognition 115 (2):268-281.
  7.  8
    Estimating Causal Strength: The Role of Structural Knowledge and Processing Effort.Michael R. Waldmann & York Hagmayer - 2001 - Cognition 82 (1):27-58.
  8.  12
    Causal Learning in Rats and Humans: A Minimal Rational Model.Michael R. Waldmann, Patricia W. Cheng, York Hagmayer & Aaron P. Blaisdell - 2008 - In Nick Chater & Mike Oaksford (eds.), The Probabilistic Mind: Prospects for Bayesian Cognitive Science. Oxford University Press.
  9.  61
    Category Transfer in Sequential Causal Learning: The Unbroken Mechanism Hypothesis.York Hagmayer, Björn Meder, Momme von Sydow & Michael R. Waldmann - 2011 - Cognitive Science 35 (5):842-873.
    The goal of the present set of studies is to explore the boundary conditions of category transfer in causal learning. Previous research has shown that people are capable of inducing categories based on causal learning input, and they often transfer these categories to new causal learning tasks. However, occasionally learners abandon the learned categories and induce new ones. Whereas previously it has been argued that transfer is only observed with essentialist categories in which the hidden properties are causally relevant for (...)
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  10.  44
    From Colliding Billiard Balls to Colluding Desperate Housewives: Causal Bayes Nets as Rational Models of Everyday Causal Reasoning.York Hagmayer & Magda Osman - 2012 - Synthese 189 (S1):17-28.
    Many of our decisions pertain to causal systems. Nevertheless, only recently has it been claimed that people use causal models when making judgments, decisions and predictions, and that causal Bayes nets allow us to formally describe these inferences. Experimental research has been limited to simple, artificial problems, which are unrepresentative of the complex dynamic systems we successfully deal with in everyday life. For instance, in social interactions, we can explain the actions of other's on the fly and we can generalize (...)
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  11. Causal Induction Enables Adaptive Decision Making.Björn Meder & York Hagmayer - 2009 - In N. A. Taatgen & H. van Rijn (eds.), Proceedings of the 31st Annual Conference of the Cognitive Science Society.
     
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  12.  37
    Hierarchical Bayesian Models as Formal Models of Causal Reasoning.York Hagmayer & Ralf Mayrhofer - 2013 - Argument and Computation 4 (1):36 - 45.
    (2013). Hierarchical Bayesian models as formal models of causal reasoning. Argument & Computation: Vol. 4, Formal Models of Reasoning in Cognitive Psychology, pp. 36-45. doi: 10.1080/19462166.2012.700321.
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  13. A Transitivity Heuristic of Probabilistic Causal Reasoning.Momme von Sydow, Björn Meder & York Hagmayer - 2009 - In N. A. Taatgen & H. van Rijn (eds.), Proceedings of the 31st Annual Conference of the Cognitive Science Society.
     
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  14. Causal Learning Through Repeated Decision Making.York Hagmayer & Björn Meder - 2008 - In B. C. Love, K. McRae & V. M. Sloutsky (eds.), Proceedings of the 30th Annual Conference of the Cognitive Science Society. Cognitive Science Society. pp. 179--184.
     
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