Proceedings of the Annual Meeting of the Cognitive Science Society

Evidence from a variety of learning tasks suggests that cuesthat are more predictive of an outcome attract greater attentionand are learned about more effectively in subsequent tasks. Wetested whether this learned predictiveness effect is due to theobjective strength of the cue-outcome association (cue-outcome correlation), or the degree to which the cue isinformative for making the correct choice on each trial (choicerelevance), by manipulating the possible outcome choicesavailable on each trial. Experiment 1 compared two sets of cuesthat were equally (and imperfectly) correlated with outcomesand showed learning biases in favor of the set of cues that hadinitially been more relevant for choices made on each trial.Experiment 2 used a more conventional learned predictivenessdesign in which the cue-outcome correlation was stronger forone set of cues (perfect predictors) than the other set (imperfectpredictors). However, here we manipulated whether or not theimperfect predictors could be used to make a correct choice,and thus whether the imperfect predictors possessed choicerelevance that was equal to or less than the perfect predictors.In this case, we found no evidence that the relevancemanipulation made any difference; learning biases towards theperfect predictor were evident regardless. The results suggestthat both cue-outcome correlation and choice relevance canlead to changes in associability and learning biases; both wereindividually sufficient but neither were necessary.