12 found
Order:
  1.  43
    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. New York: Oxford University Press.
  2.  32
    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. New York: Oxford University Press.
    Direct download  
     
    Export citation  
     
    Bookmark   21 citations  
  3.  16
    Estimating causal strength: the role of structural knowledge and processing effort.Michael R. Waldmann & York Hagmayer - 2001 - Cognition 82 (1):27-58.
  4.  46
    Self-deception requires vagueness.Steven A. Sloman, Philip M. Fernbach & York Hagmayer - 2010 - Cognition 115 (2):268-281.
  5.  88
    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 (...)
    Direct download (2 more)  
     
    Export citation  
     
    Bookmark   4 citations  
  6.  18
    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.
    Direct download  
     
    Export citation  
     
    Bookmark   6 citations  
  7.  82
    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 (...)
    No categories
    Direct download (2 more)  
     
    Export citation  
     
    Bookmark   4 citations  
  8.  85
    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 (...)
    Direct download (4 more)  
     
    Export citation  
     
    Bookmark   3 citations  
  9.  63
    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.
    Direct download (4 more)  
     
    Export citation  
     
    Bookmark   1 citation  
  10. 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.
     
    Export citation  
     
    Bookmark  
  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.
     
    Export citation  
     
    Bookmark   1 citation  
  12. 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.
     
    Export citation  
     
    Bookmark   1 citation