When 2 cues occur together and reliably predict an outcome, Ss often judge the effect of the compound as reducible to the individual effects of the elements. This elemental processing in predictive learning is perhaps the single most important aspect of most theories of human inference. Surprisingly, selectional processing was not observed in either blocking or conditioned inhibition problems. Only when the learner had past experience with another problem encouraging an elemental strategy were the expected selectional processes observed. These proactive effects of prior learning were abolished if the earlier problem required a nonadditive solution. The results suggest that configural cues were guiding predictive inferences in the absence of elemental processes.Many authors have been struck by the formal similarity of the problem of covariation detection in humans and animals (e.g., Gluck & Bower, 1988;Holyoak, Koh, & Nisbett, 1989;Shanks & Dickinson, 1987). Both organisms must learn to detect regularities in their environment and to take appropriate actions. That is, predictive signals must be identified in a stream of irrelevant cues, whether these signals predict the romantic interest of another person or patches of food for a hungry animal. These parallels raise the intriguing possibility that similar learning mechanisms may explain how humans and animals solve formally analogous problems.This possibility is encouraged when variables in the human and animal domains have corresponding effects. For example, in assessing the contingency between an action and an outcome, people are sensitive to the likelihood of the outcome in the presence versus absence of the action (e.g., Chatlosh, Neunaber, & Wasserman, 1985). The outcome is presumed to be contingent only if the action influences the background rate of occurrence of the outcome. By no means are the reported contingency effects equivalent to statistical measures of covariation. People often overestimate zero contingencies, especially if there is a high probability of the outcome (Alloy & Tabachnik, 1984). Animals show a similar sensitivity to contingency (Rescorla, 1968) and also respond inappropriately early in training when there is a nominal zero contingency (e.g., Benedict & Ayres, 1972). Shared imperfections in covariation detection like these can be explained by an associative model (e.g., Wasserman, Elek, Chatlosh, & Baker, 1993).Although there has been considerable progress in our understanding of the cognitive processes underlying predictive