The Role of Reward in Dynamic Decision Making

The present study investigates two aspects of decision making that have yet to be explored within a dynamic environment, (1) comparing the accuracy of cue-outcome knowledge under conditions in which knowledge acquisition is either through Prediction or Choice, and (2) examining the effects of reward on both Prediction and Choice. In the present study participants either learnt about the cue-outcome relations in the environment by choosing cue values in order to maintain an outcome to criterion (Choice-based decision making), or learnt to predict the outcome from seeing changes to the cue values (Prediction-based decision making). During training participants received outcome feedback and one of four types of reward manipulations: Positive Reward, Negative Reward, Both Positive + Negative Reward, No Reward. After training both groups of learners were tested on prediction and choice-based tasks. In the main, the findings revealed that cue-outcome knowledge was more accurate when knowledge acquisition was Choice-based rather than Prediction-based. During learning Negative Reward adversely affected Choice-based decision making while Positive Reward adversely affected predictive-based decision making. During the test phase only performance on tests of choice was adversely affected by having received Positive Reward or Negative Reward during training. This article proposes that the adverse effects of reward may reflect the additional demands placed on processing rewards which compete for cognitive resources required to perform the main goal of the task. This in turn implies that, rather than facilitate decision making, the presentation of rewards can interfere with Choice-based and Prediction-based decisions.