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Bramley, Neil R.; Gerstenberg, Tobias; Mayrhofer, Ralf; Lagnado, David A. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2018
A large body of research has explored how the time between two events affects judgments of causal strength between them. In this article, we extend this work in 4 experiments that explore the role of temporal information in causal structure induction with multiple variables. We distinguish two qualitatively different types of information: The…
Descriptors: Time, Causal Models, Associative Learning, Learning Processes
Lagnado, David A.; Gerstenberg, Tobias; Zultan, Ro'i – Cognitive Science, 2013
How do people attribute responsibility in situations where the contributions of multiple agents combine to produce a joint outcome? The prevalence of over-determination in such cases makes this a difficult problem for counterfactual theories of causal responsibility. In this article, we explore a general framework for assigning responsibility in…
Descriptors: Attribution Theory, Causal Models, Responsibility, Cognitive Psychology
Lagnado, David A.; Sloman, Steven A. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2006
How do people learn causal structure? In 2 studies, the authors investigated the interplay between temporal-order, intervention, and covariational cues. In Study 1, temporal order overrode covariation information, leading to spurious causal inferences when the temporal cues were misleading. In Study 2, both temporal order and intervention…
Descriptors: Time, Causal Models, Time Factors (Learning), Intervention
Sloman, Steven A.; Lagnado, David A. – Cognitive Science, 2005
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…
Descriptors: Observation, Intervention, Causal Models, Prediction
Lagnado, David A.; Sloman, Steven – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2004
Can people learn causal structure more effectively through intervention rather than observation? Four studies used a trial-based learning paradigm in which participants obtained probabilistic data about a causal chain through either observation or intervention and then selected the causal model most likely to have generated the data. Experiment 1…
Descriptors: Stimuli, Observation, Intervention, Causal Models