The study of attention is central to understanding how information is processed in cognitive systems. Modern cognitive research interprets attention as the capacity to select and enhance limited aspects of currently processed information. This chapter reviews key computational models and theoretical directions pursued by researchers trying to understand the multifaceted phenomenon of attention. A broad division is drawn between theories and models addressing the mechanisms by which attention modulates specific aspects of perception (primarily visual) and those that have focused on goal-driven and task-oriented components of attention. An area of recent activity in elaborating on the computational mechanisms of goal-driven attention concerns mechanisms by which attentional biases arise or are modulated during the course of task performance. Finally, the chapter focuses on the contrast or continuum between attentional control and automaticity, an issue that becomes crystallized when examining the distinctions between, or transitions from, novice to expert cognitive task performance.