It is widely held that there is a distinction between attentive and automatic cognitive processing. In research on attention using visual search tasks, the detection performance of human subjects in consistent mapping paradigms is generally regarded as indicating a shift, with practice, from serial, attentional, controlled processing to parallel, automatic processing, while detection performance in varied mapping paradigms is taken to indicate that processing remains under attentional control. This paper proposes a priority learning mechanism to model the effects of practice and the development of automaticity, in visual search tasks. A connectionist simulation model implements this learning algorithm. Five prominent features of visual search practice effects are simulated. These are: 1) in consistent mapping tasks, practice reduces processing time, particularly the slope of reaction times as a ftinction of the number of comparisons; 2) in varied mapping tasks, there is no change in the slope of the reaction time function; 3) both the consistent and varied effects can occur concurrently; 4) reversing the target and distractor sets produces strong interference effects; and 5) the benefits of practice are a function of the degree of consistency.