Topic: kalman filters

Uncertainty plays a critical role in reinforcement learning and decision making. However, exactly how subjective uncertainty influences behaviour remains unclear. Multi-armed bandits are a useful framework to gain more insight into this. Paired with computational tools such as Kalman filters, they allow us to closely characterize the interplay between trial-by-trial value, uncertainty, learning, and choice. In this talk, I will present recent research where we also measured participants visual fixations on the options in a multi-armed bandit task. The estimated value of each option, and the un