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show that our modeling hypotheses on cognitive processes are reasonable in some
extent.
3.5
Summary
The simulation results in both behavioral data and BOLD response shows that
the computational model of 4*4 Sudoku is reasonable and the hypotheses of
modeling are explicable. The fitness of model prediction shows that some cogni-
tive elements that affect the retrieval of heuristics. The first element is the way
of problem presentation. For a given problem like 4*4 Sudoku, participants had
been trained to try to get the answer with given seven heuristics. All partici-
pants knew the task environment well. In other words, the problem space for all
participants is supposed the same. The way of problem presentation is simplified
and the complexity of heuristics decides the cost of processes of cognition. The
second one is the complexity of heuristics like the digits distribution in dimen-
sions. This is the key factor involved in the retrieval heuristics. And the third
one is the status of goal which acts a controller of the system in the whole pro-
cesses, from encoding '?', retrieving answer to speaking it out. The goal status
transformation is also important in heuristics retrieval.
4
Conclusions
Studies on human heuristic problem solving mainly involve understanding the
retrieval, implication and selection of heuristics. This paper focused on the first
issue (i.e. the retrieval of heuristics). Two methodologies have been used to
examine the problem. The first one is ACT-R modeling based on information-
processing theory and production system, and the second one is fMRI, one of
brain imaging techniques. The outputs of ACT-R model prove that the cognitive
hypotheses are reasonable. The good fitness of theory prediction to the real
participants' data shows that the model is valid. It is obviously helpful that
combining the two methods to study human brain in complex.
Acknowledgments.
Supported by the National Natural Science Foundation of
China under Grant No.60875075, Doctoral Candidates Innovative Foundation of
Beijing University of Technology under Grant No.DCX-2009-065. We would like
to thank Lijuan Wang efforts on fMRI experiment.
References
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2. Anderson, J.R., Albert, M.V., Fincham, J.M.: Tracing Problem Solving in Real
Time: fMRI Analysis of the Subject-paced Tower of Hanoi. Journal of Cognitive
Neuroscience 17(8), 1261-1274 (2005)
