Inferences about unobserved causes in human contingency learning

REFERENCES

• Ahn , W.-K. , Marsh , J. K. and Luhmann , C. C. in press . “ Dynamic interpretations of covariation data ” . In Causal learning: Psychology, philosophy, and computation , Edited by: Gopnik , A. and Schulz , L. Oxford, , UK : Oxford University Press .
   Google Scholar
• Audi , R. 1995 . The Cambridge dictionary of philosophy , Cambridge, MA : Cambridge University Press .
   Google Scholar
• Booth , S. L. and Buehner , M. J. 2007 . Asymmetries in cue competition in forward and backward blocking designs: Further evidence for causal model theory . Quarterly Journal of Experimental Psychology , 60 : 387 – 399 .
   Web of Science ®Google Scholar
• Buehner , M. J. and Cheng , P. W. Causal induction: The power PC theory versus the Rescorla–Wagner model . Proceedings of the Nineteenth Annual Conference of the Cognitive Science Society , Edited by: Langley , P. and Shafto , M. G. pp. 55 – 60 . Hillsdale, NJ : Lawrence Erlbaum Associates, Inc .
   Google Scholar
• Buehner , M. J. , Cheng , P. W. and Clifford , D. 2003 . From covariaton to causation: A test of the assumption of causal power . Journal of Experimental Psychology: Learning, Memory, and Cognition , 29 : 1119 – 1140 .
   PubMed Web of Science ®Google Scholar
• Catena , A. , Maldonado , A. and Cándido , A. 1998 . The effect of frequency of judgement and the type of trials on covariation learning . Journal of Experimental Psychology: Human Perception & Performance , 24 : 481 – 495 .
   Web of Science ®Google Scholar
• Cheng , P. W. 1997 . From covariation to causation: A causal power theory . Psychological Review , 104 : 367 – 405 .
   Web of Science ®Google Scholar
• Cobos , P. L. , López , F. J. and Luque , D. 2007 . Interference between cues of the same outcome depends on the causal interpretation of the events . Quarterly Journal of Experimental Psychology , 60 : 369 – 386 .
   Web of Science ®Google Scholar
• Danks , D. 2003 . Equilibria of the Rescorla–Wagner model . Journal of Mathematical Psychology , 47 : 109 – 121 .
   Web of Science ®Google Scholar
• Danks , D. in press . “ Causal learning from observations and manipulations ” . In Thinking with data , Edited by: Lovett , M. and Shah , P. Mahwah, NJ : Lawrence Erlbaum Associates, Inc .
   Google Scholar
• De Houwer , J. , Vandorpe , S. and Beckers , T. 2007 . Statistical contingency has a different impact on preparation judgements than on causal judgements . Quarterly Journal of Experimental Psychology , 60 : 418 – 432 .
   PubMed Web of Science ®Google Scholar
• Gelman , S. 2003 . The essential child. Origins of essentialism in everyday thought , Cambridge, MA : Oxford University Press .
   Google Scholar
• Glymour , C. 2001 . The mind's arrow. Bayes nets and graphical causal models in psychology , Cambridge, MA : MIT Press .
   Google Scholar
• Gopnik , A. , Glymour , C. , Sobel , D. M. , Schulz , L. E. , Kushnir , T. and Danks , D. 2004 . A theory of causal learning in children: Causal maps and Bayes nets . Psychological Review , 111 : 3 – 32 .
   PubMed Web of Science ®Google Scholar
• Gopnik , A. and Meltzoff , A. N. 1997 . Words, thoughts and theories , Cambridge, MA : MIT Press .
   Google Scholar
• Gopnik , A. and Wellman , H. M. 1994 . “ The theory theory ” . In Mapping the mind: Domain specificity in cognition and culture , Edited by: Hirschfeld , L. and Gelman , S. 257 – 293 . New York : Cambridge University Press .
   Google Scholar
• Griffiths , T. L. and Tenenbaum , J. B. 2005 . Structure and strength in causal induction . Cognitive Psychology , 51 : 285 – 386 .
   PubMed Web of Science ®Google Scholar
• Hagmayer , Y. , Sloman , S. A. , Lagnado , D. A. and Waldmann , M. R. in press . “ Causal reasoning through intervention ” . In Causal learning: Psychology, philosophy, and computation , Edited by: Gopnik , A. and Schulz , L. Oxford, , UK : Oxford University Press .
   Google Scholar
• Hernstein , R. J. 1997 . The matching law , Cambridge, MA : Harvard University Press .
   Google Scholar
• Jensen , F. V. 1997 . An introduction to Bayesian networks , London : Springer .
   Google Scholar
• Keinath , A. and Krems , J. F. Anomalous data integration in diagnostic reasoning . Proceedings of the 1999 European Conference on Cognitive Scienc , Edited by: Bagnara , A. pp. 213 – 218 . Siena, , Italy : Consiglo Nationale delle Ricerche .
   Google Scholar
• Krems , J. F. and Johnson , T. Integration of anomalous data in multi causal explanations . Proceedings of the Seventeenth Annual Conference of the Cognitive Science Society , Edited by: Moore , J. D. and Lehman , J. F. pp. 277 – 282 . Hillsdale, NJ : Lawrence Erlbaum Associates, Inc .
   Google Scholar
• Kushnir , T. , Gopnik , A. , Schulz , L. and Danks , D. Inferring hidden causes . Proceedings of the Twenty-fifth Annual Conference of the Cognitive Science Society , Edited by: Langley , P. and Shafto , M. G. Mahwah, NJ : Lawrence Erlbaum Associates, Inc .
   Google Scholar
• Lober , K. and Shanks , D. R. 2000 . Is causal induction based on causal power? Critique of Cheng (1997) . Psychological Review , 107 : 195 – 212 .
   PubMed Web of Science ®Google Scholar
• Luhmann , C. C. and Ahn , W.-K. Evaluating the causal role of unobserved variables . Proceedings of the Twenty-fifth Annual Conference of the Cognitive Science Society , Edited by: Langley , P. and Shafto , M. G. Mahwah, NJ : Lawrence Erlbaum Associates, Inc .
   Google Scholar
• Meder , B. , Hagmayer , Y. and Waldmann , Y. Doing after seeing . Proceedings of the Twenty-Seventh Annual Conference of the Cognitive Science Society. Edited by: Bara , B. G. , Barsalou , L. and Bucciarelli , M. Mahwah, NJ : Lawrence Erlbaum Associates, Inc .
   Google Scholar
• Medin , D. L. and Ortony , A. 1989 . “ Psychological essentialism ” . In Similarity and analogical reasoning , Edited by: Vosniadou , S. and Ortony , A. 179 – 195 . Cambridge, , UK : Cambridge University Press .
   Google Scholar
• Myers , J. L. 1976 . “ Probability learning and sequence learning ” . In Handbook of learning and cognitive processes: Approaches to human learning and motivation , Edited by: Estes , W. K. 171 – 205 . Hillsdale, NJ : Lawrence Erlbaum Associates, Inc .
   Google Scholar
• Pearl , J. 1988 . Probabilistic reasoning in intelligent systems: Networks of plausible inference , San Francisco, CA : Morgan Kaufmann .
   Google Scholar
• Pearl , J. 2000 . Causality: Models, reasoning, and inference , Cambridge, MA : Cambridge University Press .
   Google Scholar
• Rehder , B. 2003 . A causal-model theory of conceptual representation and categorization . Journal of Experimental Psychology: Learning, Memory, and Cognition , 29 : 1141 – 1159 .
   PubMed Web of Science ®Google Scholar
• Rehder , B. and Hastie , R. 2001 . Causal knowledge and categories: The effects of causal beliefs on categorization, induction, and similarity . Journal of Experimental Psychology: General , 130 : 323 – 360 .
   PubMed Web of Science ®Google Scholar
• Rescorla , R. A. and Wagner , A. R. 1972 . “ A theory of Pavlovian conditioning: Variations in the effectiveness of reinforcement and non-reinforcement ” . In Classical conditioning II. Current research and theory , Edited by: Black , A. H. and Prokasy , W. F. 64 – 99 . New York : Appleton-Century-Crofts .
   Google Scholar
• Shanks , D. R. 1987 . Acquisition functions in contingency judgment . Learning and Motivation , 18 : 147 – 166 .
   Web of Science ®Google Scholar
• Shanks , D. R. 2007 . Associationism and cognition: Human contingency learning at 25 . Quarterly Journal of Experimental Psychology , 60 : 291 – 309 .
   PubMed Web of Science ®Google Scholar
• Shanks , D. R. , Holyoak , K. J. and Medin , D. L. 1996 . The psychology of learning and motivation: Vol. 34. Causal learning , San Diego, CA : Academic Press .
   Google Scholar
• Sloman , S. A. and Lagnado , D. A. 2005 . Do we “do”? . Cognitive Science , 29 : 5 – 39 .
   PubMed Web of Science ®Google Scholar
• Spirtes , P. , Glymour , C. and Scheines , R. 1993 . Causation, prediction and search , New York : Springer .
   Google Scholar
• Tenenbaum , J. B. and Griffiths , T. L. 2003 . “ Theory-based causal inference ” . In Advances in neural information processing systems , Edited by: Leen , T. K. , Dietterich , T. G. and Tresp , V. Vol. 15 , 35 – 42 . Cambridge, MA : MIT Press .
   Google Scholar
• Vandorpe , S. , De Houwer , J. and Beckers , T. 2007 . Outcome maximality and additivity training also influence cue competition in causal learning when learning involves many cues and events . Quarterly Journal of Experimental Psychology , 60 : 356 – 368 .
   Web of Science ®Google Scholar
• Vulkan , N. 2000 . An economist's perspective on probability matching . Journal of Economic Surveys , 14 : 101 – 118 .
   Web of Science ®Google Scholar
• Waldmann , M. R. and Hagmayer , Y. 2001 . Estimating causal strength: The role of structural knowledge and processing effort . Cognition , 82 : 27 – 58 .
   PubMed Web of Science ®Google Scholar
• Waldmann , M. R. and Hagmayer , Y. 2005 . Seeing vs. doing: Two modes of accessing causal knowledge . Journal of Experimental Psychology: Learning, Memory, and Cognition , 31 : 216 – 227 .
   PubMed Web of Science ®Google Scholar
• Wasserman , E. A. , Elek , S. M. , Chatlosh , D. L. and Baker , A. G. 1993 . Rating causal relations: Role of probability in judgments of response–outcome contingency . Journal of Experimental Psychology: Learning, Memory, and Cognition , 19 : 174 – 188 .
   Web of Science ®Google Scholar
• Wellman , H. M. 1990 . The child's theory of mind , Cambridge, MA : MIT Press .
   Google Scholar
• White , P. A. 2003 . Making causal judgments from the proportion of confirming instances: The pCI rule . Journal of Experimental Psychology: Learning, Memory, and Cognition , 29 : 710 – 727 .
   PubMed Web of Science ®Google Scholar
• Woodward , J. 2003 . Making things happen. A theory of causal explanation , Oxford, , UK : Oxford University Press .
   Google Scholar