DreamerV3 learns a world model from experiences and uses it to train an actor-critic policy from imagined trajectories. The world model encodes sensory inputs into categorical representations and predicts future representations and rewards given actions. This implementation masters a wide range of domains with a fixed set of hyperparameters, using JAX as the underlying framework.