A Model of Agential Learning Using Active Inference

Agential learning refers to the process of forming beliefs regarding one’s degree of control over actions and outcomes in their environment. We first provide an overview and evaluation of associative, statistical, and Bayesian models of agential learning. We then argue that the existing models have limitations in explaining the process of agential learning. Finally, we introduce an active inference account of agential learning, and present results from simulations. We propose that the active inference framework may provide a comprehensive model of agential learning describing three fundamental processes: (i) perception, (ii) learning, and (iii) action.