Flexible use of recent information in causal and predictive judgments

Flexible use of recent information in causal and predictive judgments (2002)

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by Helena Matute , Sonia Vegas , Pieter-jan De Marez

Venue:	Journal of Experimental Psychology: Learning, Memory, and Cognition
Citations:	9 - 4 self

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Datum	Value	Source
TITLE	Flexible use of recent information in causal and predictive judgments	INFERENCE
AUTHOR NAME	Helena Matute	SVM HeaderParse 0.2
AUTHOR NAME	Sonia Vegas	SVM HeaderParse 0.2
AUTHOR NAME	Pieter-jan De Marez	SVM HeaderParse 0.2
ABSTRACT	Associative and statistical theories of causal and predictive learning make opposite predictions for situations in which the most recent information contradicts the information provided by older trials (e.g., acquisition followed by extinction). Associative theories predict that people will rely on the most recent information to best adapt their behavior to the changing environment. Statistical theories predict that people will integrate what they have learned in the two phases. The results of this study showed one or the other effect as a function of response mode (trial by trial vs. global), type of question (contiguity, causality, or predictiveness), and postacquisition instructions. That is, participants are able to give either an integrative judgment, or a judgment that relies on recent information as a function of test demands. The authors concluded that any model must allow for flexible use of information once it has been acquired. Learning to predict the events in our environment is critical for survival. Both humans and other animals are known to learn predictive and causal relations between the events in their environment, and the question of how they do it has preoccupied philosophers and psychologists for many years.	SVM HeaderParse 0.2
YEAR	2002	INFERENCE
VENUE	Journal of Experimental Psychology: Learning, Memory, and Cognition	INFERENCE
VENUE TYPE	JOURNAL	INFERENCE
PAGES	714--725	INFERENCE
VOLUME	28	INFERENCE
CITATIONS	28 found	ParsCit 1.0