Reduced Summation with Common Features in Causal Judgments

Abstract

In three experiments human participants received training in a causal judgment task. After learning which patterns were associated with an outcome, participants rated the likelihood of the outcome in the presence of a novel combination of the patterns. The first two experiments used two conditions in which two visual patterns were associated with the outcome. In one condition these patterns shared a common feature. The third experiment only used the common feature condition. According to an elemental theory ( Rescorla & Wagner, 1972) the response to the novel test pattern should have exceeded that made to the individual training patterns, a summation effect, and this effect should have been reduced by the addition of a common feature. Summation was observed but since the common feature condition abolished, rather than merely reduced, summation the results were not consistent with the Rescorla-Wagner Model (RWM) nor with a configural alternative ( Pearce, 1994). Instead, it is necessary to consider models which allow the possibility of both elemental and configural strategies in causal learning. The Replaced Elements Model ( Wagner, 2003) is a development of the RWM which can best predict the patterns of summation and summation failure in these experiments.