Bursting with Error: Dealing with unexpected prediction error in Babybots
Our research builds on and adds to the prediction processing theory, specifically to model updating and model revision. We propose a hyperparameter approach to model updating at the computational level, designed to add precision to beliefs, which we tested via computer simulations. We also introduce the concept of unexpected high prediction error, which can be used as a signal to revise the generative model of agents. The latter links two of the proposed methods the brain uses to reduce future prediction error.
Faculteit der Sociale Wetenschappen