Before revision:  In contrast to analogous frameworks - by operating in a pure belief-based setting (free energy functional of beliefs about states) - active inference agents can carry out epistemic exploration and naturally account for uncertainty about their environment  .
After revision:  In contrast to analogous frameworks - by operating in a pure belief-based setting (free energy functional of beliefs about states) - active inference agents can carry out epistemic exploration and naturally account for uncertainty about their environment - in a Bayes optimal fashion. We make these properties explicit by showing that the active inference agent's ability to carry out online planning, in a pure-belief setting, enables it to act optimally, given the non-stationary dynamics of an environment when compared to both Q-learning and Bayesian model-based reinforcement learning agents .