The first talk in the Social, Economic, and Decision Psychology research seminar will be given at 12:00 on Thursday 4 March by Ori Plonsky of the Technion Israel Institute of Technology. The talk will be totally virtual, streamed live through Zoom.

Similarity-based learning and the wavy recency effect of rare events

Many behavioral phenomena can be the product of a tendency to rely on small samples of past experiences. Previous studies suggest that this can be a product of a cognitively efficient tendency to rely on the most recent outcomes. Congruently, the most popular models of learning assume that people mostly rely on a few recent outcomes. In this talk, I will review research suggesting a very different explanation: People rely on a small set of the most similar past experiences. My investigation explores settings of repeated binary choice with feedback. I will present a model, designed for these settings, that judges similarity as a function of sequential patterns of outcomes. A computational analysis shows this model can be extremely effective across wide classes of dynamic decision settings (more effective than basic reinforcement learning models).It further shows that in static settings with rare events the model predicts a unique wavy recency pattern. Empirical analysis of multiple datasets (including decisions from experience with full or with partial feedback, probability learning tasks, and repeated decisions under risk with feedback) support this wavy recency prediction, a pattern that was ignored by prior research and violates the basic assumption of recency in popular learning models. a pattern that was ignored by prior research and violates the basic assumption of recency in popular learning models. a pattern that was ignored by prior research and violates the basic assumption of recency in popular learning models.

Supporting literature: Plonsky, O., Teodorescu, K., & Erev, I. (2015). Reliance on small samples, the wavy recency effect, and similarity-based learning. Psychological Review, 122(4), 621.