Results 1 - 10
of
38
The advantage of timely intervention
- Journal of Experimental Psychology: Learning, Memory, and Cognition
, 2004
"... All in-text references underlined in blue are linked to publications on ResearchGate, letting you access and read them immediately. ..."
Abstract
-
Cited by 62 (5 self)
- Add to MetaCart
All in-text references underlined in blue are linked to publications on ResearchGate, letting you access and read them immediately.
Beyond covariation: Cues to causal structure
- IN A. GOPNIK & L. SCHULZ (EDS.), CAUSAL LEARNING: PSYCHOLOGY, PHILOSOPHY, AND COMPUTATION
, 2006
"... ..."
Seeing versus doing: Two modes of accessing causal knowledge
- Journal of Experimental Psychology: Learning, Memory, and Cognition
, 2005
"... The ability to derive predictions for the outcomes of potential actions from observational data is one of the hallmarks of true causal reasoning. We present four learning experiments with deterministic and probabilistic data showing that people indeed make different predictions from causal models, w ..."
Abstract
-
Cited by 35 (11 self)
- Add to MetaCart
The ability to derive predictions for the outcomes of potential actions from observational data is one of the hallmarks of true causal reasoning. We present four learning experiments with deterministic and probabilistic data showing that people indeed make different predictions from causal models, whose parameters were learned in a purely observational learning phase, depending on whether learners believe that an event within the model has been merely observed (“seeing”) or was actively manipulated (“doing”). The predictions reflect sensitivity both to the structure of the causal models and to the size of their parameters. This competency is remarkable because the predictions for potential interventions were very different from the patterns that had actually been observed. Whereas associative and probabilistic theories fail, recent developments of causal Bayes net theories provide tools for modeling this competency. Causal knowledge underlies our ability to predict future events, to explain the occurrence of present events, and to achieve goals by means of actions. Thus, causal knowledge belongs to one of our most central cognitive competencies. However, the nature of causal knowledge has been debated. A number of philosophers and
Mechanisms of predictive and diagnostic causal induction
- Journal of Experimental Psychology: Animal Behavior Processes
, 2002
"... In predictive causal inference, people reason from causes to effects, whereas in diagnostic inference, they reason from effects to causes. Independently of the causal structure of the events, the temporal structure of the information provided to a reasoner may vary (e.g., multiple events followed by ..."
Abstract
-
Cited by 22 (1 self)
- Add to MetaCart
(Show Context)
In predictive causal inference, people reason from causes to effects, whereas in diagnostic inference, they reason from effects to causes. Independently of the causal structure of the events, the temporal structure of the information provided to a reasoner may vary (e.g., multiple events followed by a single event vs. a single event followed by multiple events). The authors report 5 experiments in which causal structure and temporal information were varied independently. Inferences were influenced by temporal structure but not by causal structure. The results are relevant to the evaluation of 2 current accounts of causal induction, the Rescorla–Wagner (R. A. Rescorla & A. R. Wagner, 1972) and causal model theories (M. R. Waldmann & K. J. Holyoak, 1992). Knowledge about covariations between events is one of the most basic forms of inferential knowledge. It confers on its pos-sessor a very powerful tool to reduce uncertainty about the occur-rence of events. For example, an organism may predict the pres-ence of future events from knowing whether a particular present event has occurred. Such inferential knowledge appears to be within the scope of numerous species, as the study of animal
The Role of Causality in Judgment Under Uncertainty
"... Leading accounts of judgment under uncertainty evaluate performance within purely statistical frameworks, holding people to the standards of classical Bayesian (Tversky & Kahneman, 1974) or frequentist (Gigerenzer & Hoffrage, 1995) norms. We argue that these frameworks have limited ability t ..."
Abstract
-
Cited by 21 (0 self)
- Add to MetaCart
(Show Context)
Leading accounts of judgment under uncertainty evaluate performance within purely statistical frameworks, holding people to the standards of classical Bayesian (Tversky & Kahneman, 1974) or frequentist (Gigerenzer & Hoffrage, 1995) norms. We argue that these frameworks have limited ability to explain the success and flexibility of people's real-world judgments, and propose an alternative normative framework based on Bayesian inferences over causal models. Deviations from traditional norms of judgment, such as "base-rate neglect", may then be explained in terms of a mismatch between the statistics given to people and the causal models they intuitively construct to support probabilistic reasoning. Four experiments show that when a clear mapping can be established from given statistics to the parameters of an intuitive causal model, people are more likely to use the statistics appropriately, and that when the classical and causal Bayesian norms differ in their prescriptions, people's judgments are more consistent with causal Bayesian norms.
Interpreting Causality
- in the Health Sciences,‖ International Studies in the Philosophy of Science
, 2007
"... Perhaps the key philosophical questions concerning causality are the follow-ing: • what are causal relationships? • how can one discover causal relationships? ..."
Abstract
-
Cited by 16 (6 self)
- Add to MetaCart
Perhaps the key philosophical questions concerning causality are the follow-ing: • what are causal relationships? • how can one discover causal relationships?
Webbased experiment control software for research and teaching on human learning. Behavior Research Methods
, 2007
"... In this article we describe some of the experimental software we have developed for the study of associative human learning and memory. All these programs have the appearance of very simple video games. Some of them use the participants ’ behavioral responses to certain stimuli during the game as a ..."
Abstract
-
Cited by 13 (8 self)
- Add to MetaCart
(Show Context)
In this article we describe some of the experimental software we have developed for the study of associative human learning and memory. All these programs have the appearance of very simple video games. Some of them use the participants ’ behavioral responses to certain stimuli during the game as a dependent variable for measuring their learning of the target cue-outcome associations. Some others explicitly ask participants to rate the degree of relationship they perceive between the cues and the outcomes. These programs are implemented in Web pages using JavaScript, which allows their use both in traditional laboratory experiments as well as in Internet-based experiments. The psychology of learning is a research area that has usually been investigated with nonhuman animals and in which, traditionally, there existed too many procedural and ethical problems to conduct experiments with humans. However, human learning is today a flourishing research area in which many interesting effects are being reported around the world (see, e.g., De Houwer &
Contrasting predictive and causal values of predictors and of causes. Learn Behav 2005; 33(2
"... ABSTRACT Three experiments examined human processing of stimuli as predictors and causes. In Experiments 1A and 1B, two serial events that both preceded a third were assessed as predictors and as causes of the third event. Instructions successfully provided scenarios in which one of the serial (tar ..."
Abstract
-
Cited by 9 (4 self)
- Add to MetaCart
(Show Context)
ABSTRACT Three experiments examined human processing of stimuli as predictors and causes. In Experiments 1A and 1B, two serial events that both preceded a third were assessed as predictors and as causes of the third event. Instructions successfully provided scenarios in which one of the serial (target) stimuli was viewed as a strong predictor but as a weak cause of the third event. In Experiment 2, participants' preexperimental knowledge was drawn upon in such a way that two simultaneous antecedent events were processed as predictors or causes, which strongly influenced the occurrence of overshadowing between the antecedent events. Although a tendency toward overshadowing was found between predictors, reliable overshadowing was observed only between causes, and then only when the test question was causal. Together with other evidence in the human learning literature, the present results suggest that predictive and causal learning obey similar laws, but there is a greater susceptibility to cue competition in causal than predictive attribution.
The psychophysics of contingency assessment
- Journal of Experimental Psychology: General
, 2008
"... The authors previously described a procedure that permits rapid, multiple within-participant evaluations ..."
Abstract
-
Cited by 8 (4 self)
- Add to MetaCart
(Show Context)
The authors previously described a procedure that permits rapid, multiple within-participant evaluations
Judging relationships between events: how do we do it
, 2005
"... models provided the best account of data generated in tasks that require human observers to judge the relationship between binary events. In the intervening years, new data have been reported that provide evidence for higherorder processes. Some have argued that these new data pose a serious threat ..."
Abstract
-
Cited by 7 (6 self)
- Add to MetaCart
models provided the best account of data generated in tasks that require human observers to judge the relationship between binary events. In the intervening years, new data have been reported that provide evidence for higherorder processes. Some have argued that these new data pose a serious threat to the viability of the associative account. The purpose of the present paper is to review this evidence and to assess the severity of this threat. In 1978, Brooks described the interaction between analytic and nonanalytic processes, and argued that “there are many factors that push a person’s strategy toward one end of the scale or another – that is, toward learning individuals by codings that are designed to retain the item’s individuality, or toward tracking the validity of characteristics of the stimulus
