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A sub-symbolic model of the cognitive processes of re-representation and insight

Published: 26 October 2009 Publication History

Abstract

We present a sub-symbolic computational model for effecting knowledge re-representation and insight. Given a set of data, manifold learning is used to automatically organize the data into one or more representational transformations, which are then learned with a set of neural networks. The result is a set of neural filters that can be applied to new data as re-representation operators.

References

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N. Bonnardel. Creativity in design activities:the role of analogies in a constrained cognitive environment. In Proceedings of the Conference on Creativity and Cognition, pages 158--165, 1999.
[2]
M. Elton. Artificial creativity: enculturing computers. Leonardo, pages 207--213, 1995.
[3]
M. Gashler, D. Ventura, and T. Martinez. Iterative non-linear dimensionality reduction with manifold sculpting. Advances in Neural Information Processing Systems, 19, 2007.
[4]
S. Ohlsson. Information-processing explanations of insight and related phenomenon. Advances in the Psychology of Thinking, pages 1--44, 1992.

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cover image ACM Conferences
C&C '09: Proceedings of the seventh ACM conference on Creativity and cognition
October 2009
520 pages
ISBN:9781605588650
DOI:10.1145/1640233

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 26 October 2009

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Author Tags

  1. cognitive model
  2. insight
  3. re-representation

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C&C '09
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C&C '09: Creativity and Cognition 2009
October 26 - 30, 2009
California, Berkeley, USA

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Overall Acceptance Rate 108 of 371 submissions, 29%

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