2000
DOI: 10.3758/bf03213001
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Blocking and backward blocking involve learned inattention

Abstract: Four experiments examine blocking of associative learning by human participants in a disease diagnosis procedure. The results indicate that after a cue is blocked, subsequent learning about the cue is attenuated. This attenuated learning after blocking is obtained for both standard blocking and for backward blocking. Attenuated learning after blocking cannot be accounted for by theories such as the Rescorla-Wagner model that rely on lack of learning about a redundant cue, nor can it be accounted for by extensi… Show more

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Cited by 167 publications
(227 citation statements)
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“…Kruschke (2001) proposed a model (EXIT) that "provides a framework wherein Mackintosh's (1975) formulas for attention learning and for association learning derive from the same motivation, gradient descent on error" (Kruschke, 2001). He was able to use his model to fit human data from an earlier behavioral study (Kruschke and Blair, 2000). The architecture of the EXIT model allows it to simulate the control of attention over associative learning to an exceptional degree.…”
Section: Nih Public Accessmentioning
confidence: 99%
See 3 more Smart Citations
“…Kruschke (2001) proposed a model (EXIT) that "provides a framework wherein Mackintosh's (1975) formulas for attention learning and for association learning derive from the same motivation, gradient descent on error" (Kruschke, 2001). He was able to use his model to fit human data from an earlier behavioral study (Kruschke and Blair, 2000). The architecture of the EXIT model allows it to simulate the control of attention over associative learning to an exceptional degree.…”
Section: Nih Public Accessmentioning
confidence: 99%
“…We used the Leabra framework for activation dynamics and learning (O'Reilly and Munakata, 2000;O'Reilly, 1998), which provides a coherent This model is capable of simulating human performance in the above mentioned fictitious diagnosis task (Kruschke and Blair, 2000). Error-driven weight changes are determined by the generalized recirculation algorithm (GeneRec, O'Reilly, 1996), which is a central component of the Leabra framework.…”
Section: Details Of the Modelmentioning
confidence: 99%
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“…It is not the case that a list of vehicles is a tone, so the task did not involve hierarchical classification. Similar prediction tasks have been used in many other studies on blocking, for example, Chapman and Robbins (1990) used a stock market prediction paradigm; Kruschke and Blair (2000) used symptoms that predict diseases; and Shanks (1985) used different weapons that cause tanks to explode. Without the act of classification, participants might have considered inferences a less likely prospect, thereby reducing the incentive to learn more features.…”
Section: Why Learning Categories Is Different From Learning To Predicmentioning
confidence: 99%