Literature DB >> 21702766

Do We "do"?

Steven A Sloman1, David A Lagnado.   

Abstract

A normative framework for modeling causal and counterfactual reasoning has been proposed by Spirtes, Glymour, and Scheines (1993; cf. Pearl, 2000). The framework takes as fundamental that reasoning from observation and intervention differ. Intervention includes actual manipulation as well as counterfactual manipulation of a model via thought. To represent intervention, Pearl employed the do operator that simplifies the structure of a causal model by disconnecting an intervened-on variable from its normal causes. Construing the do operator as a psychological function affords predictions about how people reason when asked counterfactual questions about causal relations that we refer to as undoing, a family of effects that derive from the claim that intervened-on variables become independent of their normal causes. Six studies support the prediction for causal (A causes B) arguments but not consistently for parallel conditional (if A then B) ones. Two of the studies show that effects are treated as diagnostic when their values are observed but nondiagnostic when they are intervened on. These results cannot be explained by theories that do not distinguish interventions from other sorts of events. 2005 Lawrence Erlbaum Associates, Inc.

Entities:  

Year:  2005        PMID: 21702766     DOI: 10.1207/s15516709cog2901_2

Source DB:  PubMed          Journal:  Cogn Sci        ISSN: 0364-0213


  17 in total

1.  Causal models frame interpretation of mathematical equations.

Authors:  Daniel Mochon; Steven A Sloman
Journal:  Psychon Bull Rev       Date:  2004-12

2.  The influence of causal information on judgments of treatment efficacy.

Authors:  Jennelle E Yopchick; Nancy S Kim
Journal:  Mem Cognit       Date:  2009-01

3.  Inferring interventional predictions from observational learning data.

Authors:  Bjorn Meder; York Hagmayer; Michael R Waldmann
Journal:  Psychon Bull Rev       Date:  2008-02

4.  Classification as diagnostic reasoning.

Authors:  Bob Rehder; Shinwoo Kim
Journal:  Mem Cognit       Date:  2009-09

5.  Failures of explaining away and screening off in described versus experienced causal learning scenarios.

Authors:  Bob Rehder; Michael R Waldmann
Journal:  Mem Cognit       Date:  2017-02

Review 6.  Reasoning about causal relationships: Inferences on causal networks.

Authors:  Benjamin Margolin Rottman; Reid Hastie
Journal:  Psychol Bull       Date:  2013-04-01       Impact factor: 17.737

7.  Bayes and blickets: effects of knowledge on causal induction in children and adults.

Authors:  Thomas L Griffiths; David M Sobel; Joshua B Tenenbaum; Alison Gopnik
Journal:  Cogn Sci       Date:  2011-10-04

8.  Causal reasoning without mechanism.

Authors:  Selma Dündar-Coecke; Gideon Goldin; Steven A Sloman
Journal:  PLoS One       Date:  2022-05-13       Impact factor: 3.752

9.  The role of learning data in causal reasoning about observations and interventions.

Authors:  Björn Meder; York Hagmayer; Michael R Waldmann
Journal:  Mem Cognit       Date:  2009-04

10.  The trajectory of counterfactual simulation in development.

Authors:  Jonathan F Kominsky; Tobias Gerstenberg; Madeline Pelz; Mark Sheskin; Henrik Singmann; Laura Schulz; Frank C Keil
Journal:  Dev Psychol       Date:  2021-02
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.