Predicting risk in a multiple stimulus-reward environment

Abstract

Recently, neurobiological evidence has emerged of risk prediction along the lines of simple reinforcement learning. This evidence, however, is limited to one-step-ahead risk, namely, the uncertainty involved in the next forecast or reward. However, it appears that multistep prediction risk is more relevant. Multiple stimuli may all predict the same future reward or a sequence of future rewards, and only the risk of the total reward is relevant. It is known that subjects are indeed interested in predicting the total reward (sum of the discounted future rewards), and that learning of the expected total reward accords with the temporal differencing algorithm. Complex extensions of simple reinfo..