Learning Involves Attention

@inproceedings{Kruschke2000LearningIA,
  title={Learning Involves Attention},
  author={John K. Kruschke},
  year={2000}
}
LEARNING INVOLVES ATTENTION 2 Attention in learning One of the primary factors in the resurgence of connectionist modeling is these models’ ability to learn input-output mappings. Simply by presenting the models with examples of inputs and the corresponding outputs, the models can learn to reproduce the examples and to generalize in interesting ways. After the limitations of perceptron learning (Minsky & Papert, 1969; Rosenblatt, 1958) were overcome, most notably by the backpropagation… CONTINUE READING

Citations

Publications citing this paper.
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View 3 Excerpts
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References

Publications referenced by this paper.
Showing 1-10 of 38 references

Neural networks and physical systems with emergent collective computational abilities.

Proceedings of the National Academy of Sciences of the United States of America • 1982
View 4 Excerpts
Highly Influenced

Attention-like’ processes in classical conditioning

L. J. Kamin
Miami symposium on the prediction of behavior: Aversive stimulation, • 1968
View 5 Excerpts
Highly Influenced

The Adaptive Character of Thought

J. R. Anderson
1990
View 3 Excerpts
Highly Influenced

Selective attention in animal discrimination learning.

The Journal of general psychology • 2000
View 1 Excerpt

A model of probabilistic category learning.

Journal of experimental psychology. Learning, memory, and cognition • 1999
View 1 Excerpt

Shifting attention in cued recall

S. Dennis, J. K. Kruschke
Australian Journal of Psychology, • 1998
View 1 Excerpt

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