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 subsymbolic 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
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