Although connectionist models have provided insights into the nature of perception and motor control, connectionist accounts of higher cognition seldom go beyond an implementation of traditional symbol-processing theories. We describe a connectionist constraint satisfaction model of how people solve anagram problems. The model exploits statistics of English orthography, but also addresses the interplay of sub symbolic and symbolic computation by a mechanism that extracts approximate symbolic representations (partial orderings of letters) from subsymbolic structures and injects the extracted representation back into the model to assist in the solution of the anagram. We show the computational benefit of this extraction-injection process and discuss its relationship to conscious mental processes and working memory. We also account for experimental data concerning the difficulty of anagram solution based on the orthographic structure of the anagram string and the target word.
[1]
M. S. Mayzner,et al.
Anagram solution times: a function of letter order and word frequency.
,
1958,
Journal of experimental psychology.
[2]
M. S. Mayzner,et al.
Anagram Solution Times: A Function of Transition Probabilities
,
1959
.
[3]
M. S. Mayzner,et al.
Anagram solution times: a function of word transition probabilities.
,
1962,
Journal of experimental psychology.
[4]
Richard Sinkhorn.
A Relationship Between Arbitrary Positive Matrices and Doubly Stochastic Matrices
,
1964
.
[5]
H. Kucera,et al.
Computational analysis of present-day American English
,
1967
.