The ACT-R production-system theory (Anderson, 1993) has been extended to include a theory of visual attention and pattern recognition. Production rules can direct attention to primitive visual features in the visual array.
When attention is focused on a region, features in that
region can be synthesized into declarative chunks.
Assuming a time lo switch attention of about 200 msec, this
model proves capable of simulating the results from a
number of the basic studies of visual attention. W e have
extended this model to complex problem-solving like
equation solving where we have shown that an important
component of learning is acquiring more efficient strategies
for scanning the problem.
