The importance of memory in retrospective revaluation learning

Abstract

Retrospective revaluation— learning about implied but unpresented cues— poses one of the greatest challenges to classical learning theories. Whereas theorists have revised their models to accommodate revaluation, the empirical reliability of the phenomenon remains contentious. I present two sets of experiments that examine revaluative learning under different but analogous experimental protocols. Results provided mixed empirical evidence that is difficult to interpret in isolation. To address the issue, I apply two computational models to the experiments. An instance-based model of associative learning (Jamieson et al., 2012) predicts retrospective revaluation and anticipates participant behaviour in one set of experiments. An updated classical learning model (Ghirlanda, 2005) fails to predict retrospective revaluation, but anticipates participant behaviour in the other set of experiments. I argue that retrospective revaluation emerges as a corollary of basic memorial processes and discuss the empirical and theoretical implications.