Memory patterns for choice adaptation in dynamic environments
An important aspect of making good decisions is the ability to adapt to changes in the values of available options. Research suggests that we are poor at changing behavior and adapting our choices successfully. This work contributes to clarifying the role of memory on learning and successful adaptation to changing decision environments. We test the effects of the direction of change and the type of feedback using a decisions from experience binary choice task, where individuals learn the outcomes and their associated probabilities from feedback received after selecting between available choice options. The results revealed a robust effect of the direction of change: risk that becomes more rewarding over time is harder to detect than risk that becomes less rewarding over time; and even with full information about the outcomes of choice options people showed sub-optimal adaptation to change. We rely on three distinct computational models to interpret the role of memory on learning and adaptation. The distributions of individual model parameters were analyzed in relation to participants' ability to successfully adapt to the changing conditions of the various decision environments. Consistent across the three models and two distinct data sets (our experimental data and other researchers' data), results revealed the value of recency as an individual memory component for choice adaptation. Individuals relying more on recent experiences were more successful at adapting to change, regardless of the direction of change. We explain the value and limitations of these findings as well as opportunities for future research.