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Most current perceptual learning (PL) theories neglect several critical components of the cognitive architecture, including the necessary mechanisms for categorization, decision making, and top-down control. The resulting gap is evident in the mainstream models of PL, which can account for the gradual improvement in a fixed stimulus environment but not for the intricate patterns of specificity and transfer from one environment to another. The perceptual categorization (PC) literature has identified mechanisms that can fill this gap. The emerging consensus in this literature is that human category learning is mediated by multiple distinct (but partially overlapping) systems. One system is explicit, involves verbal rules, working memory, and executive attention. This system supports greater generalization to novel stimuli and tasks. Another system is implicit, learns stimulus-response associations via reinforcement learning …